Enabling AI-powered customer-centric strategies for insurers

The insurance industry is under intense pressure to reinvent itself as rising customer expectations and rapid advances in AI redefine how value is created.  

In this episode of Reinventing Insurance, Rick Chavez, Oliver Wyman partner and leader of CustomerFirst, talks about putting customers at the center of AI‑enabled reinvention. Drawing on his experience leading large-scale technology transformations and innovation, Rick explains why insurers should start at the endpoint of the demand chain, take explicit positions on where to play, and reallocate management attention across four operating zones: performance, productivity, transformation, and incubation.  

The conversation walks through the “AI trifecta” for customer value, the trade-offs between being a demand aggregator, an ecosystem orchestrator, or a component supplier, and how AI can make personalized financial wellness and retirement solutions more accessible and affordable. 

Key topics include:

• Prioritizing which business areas to modernize, which to manage into obsolescence, and where to place one material bet at a time. 
• How to design operating models, incentives, and accelerators to test, learn, and scale AI‑driven customer propositions. 
• Practical thinking on demand aggregation, ecosystem orchestration, and building component products that plug into broader customer solutions. 

This episode is part of our Reinventing Insurance series, a series that explores best practices for taking a CustomerFirst approach to innovation within Insurance. Throughout this series, host Paul Ricard discusses lessons, challenges, and new ways of working with guests who will share their first-hand experiences.

Subscribe for more on: Apple Podcasts | Spotify 

Putting customers first as AI reshapes the insurance future

Paul Ricard 

Welcome to Reinventing Insurance. Today, I have the pleasure of welcoming Rick Chavez, partner and leader of CustomerFirst at Oliver Wyman. Welcome, Rick. 

Rick Chavez 

Thank you, Paul. It’s great to be with you. 

Paul 

Rick, you’re not foreign to the Reinventing Insurance Podcast. I think you recorded an episode with my colleague, Mick Maloney, a little while ago. 

Rick 

That was fun. 

Paul  

We’re going to look to top that today. For those who haven’t listened to it, Rick previously talked about customer-led reinvention, his experience with the Microsoft transformation from the inside, and many other themes. We’ll have a few callbacks to these as we talk today, but our focus is going to be about being customer-first in the age of AI and where insurance goes next. Before we unravel what we’re about to discuss today, we’d love for you to briefly tell us about yourself, Rick. 

Rick 

The place we’re in now is so fascinating to me. I dabbled in what was then called an ARPAnet – now called the internet – before it was even a commercial phenomenon. If you can imagine, I’m that old. I was also dabbling with early AI, and that is another one of these curiosities, because a lot of the algorithmic innovation that we are able to enjoy now, in terms of its activation and applicability, was actually pushed hard in the 80s, but it was back in a time when we were so completely wrong about how to use it. Our theory about using these algorithms for good was not wrong; it was simply at the wrong time. Watching things evolve through the years and seeing the evolution of technology has first sobered me, and still broadly encouraged me and made me an optimist. And I’m still an optimist, Paul. It’s sometimes hard to maintain optimism, but I’m still a glass-half-full kind of person. 

In terms of my story, I stumbled into management consulting out of college. I found that I was reasonably good at it, and I liked it. What was the most interesting thing about it, for me, was that it was a great vantage point to see things in the world that you want to fix, or that you think just don’t make sense. So, I jumped out, did a startup, sold that, then went back to consulting to detox. Found another idea, jumped out and built a company at a time I call ”the great happiness internet 1.0”. All boats are rising. It was actually not a time I predicted. I was just building a great company that was hopefully going to do great things. Then the dotcom bomb was quite painful at the time, but incredibly informative, like an incredibly important learning experience for me. I took some of the ideas that I just couldn’t let go of, and they stuck with me as I went west.  

I was on the East Coast for a long time building the startups. I went west and got to work very closely with Jeff Moore (Geoffrey A. Moore), who many people know is the guy who wrote “Crossing the Chasm”, and is often thought of as the father of innovation. He is very well known on the West Coast and tech companies, but completely unknown on the East Coast. We both got very interested around the same time in innovation at scale – me from having been a startup fellow, and Jeff from having been a venture investor. We were interested not in the challenge of being a startup, when you’re being incentivized and pushed to grow with no existing stakeholder commitments. That’s what startups are.  

What happens when you’re Cisco or SAP or Yahoo or Adobe, which were clients, where the company has grown to a place, and then growth has stalled out? How do you reignite the engines of growth? I tell you that because that passion or that interest became a passion, and it stuck with me to the present. It took me through two tours of duty, one at Adobe launching what was then called Customer Experience Management and morphed into the Marketing Cloud Business of today, which is amazing. Then, as you mentioned, I was part of the transformation effort at Microsoft as Steve Ballmer handed the keys to Satya (Nadella, CEO of Microsoft). I got there by having friends at Yahoo who had reported themselves as the search team at Microsoft. 

I brought that thinking about dealing with disruption and living through transformation to my work at Oliver Wyman. CustomerFirst, to me, is really all about dealing with disruption, with a very strong view that if you start at the endpoint of a demand chain, where people are either in a workflow or at home or on the go, have big pressing problems to be solved, which could be solved better with a digital experience powered by data. That essential thesis of dealing with disruption, by looking at customers’ problems, I would argue has been a passion pre-Oliver Wyman, but certainly has been a passion as I’ve been here. 

Paul  

You’re basically threading the needle with what we’re about to discuss. You’re helping large incumbents dealing with disruption and with innovation at scale, which I think you’re starting to allude to – there is a method to the madness. 

Rick 

There is a method to the madness. I do like to say that the best entrepreneurs, the best innovators, are the most disciplined people you’ll meet. It seems to be a conundrum because I think many people who work in innovation think that this is fun. Truthfully, if you’re doing it in its truest form, it probably hurts. And that’s probably just about right, because it should be a very systematic, thoughtful test-and-learn discipline approach. I think the doing of it, and doing it right, is critically important and is something a lot of our clients are still developing and working on. 

Paul 

It’s not just the free soft drinks and the sneakers in the open space. It certainly seems like there are a lot of tectonic shifts that are happening. I know you like to talk about the collision of megatrends, and it feels like this is something that is continuing to happen and accelerate. Can you tell us a little bit what’s happening and what feels different? 

Rick 

Let me start by first saying some of what’s happening now was predictable. Any disruption, if it truly is a disruption – and you mentioned this is a collision of megatrends – that needs shifts in behavior, along with maybe societal, political, and regulatory things that are happening. Technology, I like to think of it more as a tailwind as opposed to the main event. The reason is that if you stare at technology as is the case right now in this AI moment, no matter what we say about what will be three months from now, we would be completely wrong. 

If you look at that collision and you say, all right, what is enduring about humans in their work and their attitudes and approaches to digital technology that either allows more of what they want, and less of what they don’t want to be part of their lives. I would say, first of all, that’s enduring. I’m going to come back to that. Second, that’s what’s so radically different about now versus then. We’ve never had as much digital familiarity. If you think about it, you have extraordinary familiarity with all things digital. We carry around supercomputers in our pockets. They’re connected as if they’re another finger and appendage. 

The second thing is connectivity. Pervasive connectivity. If you think about what’s happened in evolution after evolution, we have 5G, we have fiber. These things really, really matter because it means that those edge devices can do more, and they can do more that then help us be more. You have this context of pervasive connectivity that allows for very rich experiences, which we expect, and we actually want them to be intelligent. I will assert that most of the experiences have not been intelligent. Most of what we say about smartphones is, frankly, more dumb than smart. I’m sorry to say that. But the reason I say that, now that intelligence can be pushed out in the AI economy, you have people hungry for that thing and having expected it already. So that’s why this meteoric adoption of all things chat, whether it’s OpenAI or Claude or Gemini or OpenClaw, why does it look like it's instant? I think it’s because people have been expecting this kind of engagement with the world for a very long time. 

Think about it this way. You and I have been taught to use a keyboard. We’ve been taught to use our thumbs [for smartphone keyboards]. Neither of those things is particularly human. We’re okay with them, but they’re not particularly human. In this world, what’s showing up is the other thing that’s happening with adoption, making it human and natural, like the interface is my voice. This, too, is such a stunning thing because in 2001 or 2002, I was CEO of the first multimodal company that invented multimodal. We thought then, too, that it was going to get dispersed quickly. Think about how long it took. It’s this NLP natural language interaction model with deep intelligence embedded in the fabric of the world, and its ability to be dispersed and then onboarded into our lives is completely different. That is a phenomenon that is unique to this moment. 

Paul 

You are saying that it’s so enduring, and people are experiencing this at scale in their day-to-day lives. What is interesting is that there is an expectation that if a company is going to engage with me, either to solve my problem, to sell me something, or to interact with me, it’s going to feel the same way these things have felt. I would love your take on this. It feels very similar, for example, to the iPhone moment when the iPhone came out. Now, suddenly, if a company is not engaging with someone through an app, you are dead on arrival. The web 1.0 interface was… 

Rick 

became the mobile app. Exactly. That’s 100%. 

Paul 

That’s one thing. At the same time – and I would love your take on this – what is also interesting is that the pace of change is so rapid that if you got used to something two months ago, it is very, very different now. I’m also linking this to the expectation you would have from corporate, where you need to get up with the program more and more quickly. 

Rick  

The cycle time changes. Let’s take these two things because there’s a conundrum in there. One is that some things are enduring, which is to say that they’re not changing, and what does that mean? Then there’s an enormous amount of change in the cycle time, which has never been faster. We have both these things at the same time. 

I think, first, let’s take the enduring one. I do believe that the big vexing problems in the world are largely still underserved. Let me put my marketer’s hat on. Let’s pretend I’m back in the adtech days that I came from. One of the nirvanas was – if Paul’s driving along home, and it’s been a long day, and he was expected to be the dinner preparer. There’s no way he is going to be able to do that in time. But I know that Paul takes a certain route and has a certain expectation. He’s a little late actually getting home. I wonder if I could surface an offer to him to stop at some really interesting place that has the cuisine that he can pick up at home. Would that feel like magic to you that it not only knows you and your habits, but that in fact you’re kind of anxious and a little bit upset at yourself that you’re getting home late. That is an example of intelligence serving you a thing that might make a lot of sense, that you can then wrap around that moment to do something you would otherwise not have been able to do. That is the solving of a problem. And that’s been a marketer’s nirvana for a very long time. 

I think there’s a whole range of problems like that. The new intelligence environment and the ambient intelligence should be unleashed. There are still a lot of these big problems that are not solved. Like we’ve talked about this a lot: how do I solve for retirement? In my case, it might be very complex. My spouse might have one idea. I might have another. We might have to think about our kids, maybe with the sandwich generation, there are all these different kinds of considerations. No one is exactly the same. There are patterns that may rhyme, but they’re not explicitly the same. If I look at that problem, I would say, Jeez, [I would love to have] some intelligence around nudging me in one direction or another, or alerting me, or even making it simple to have a unified view of my financials. These are nontrivial problems.  

So, if I look at what the undiscovered country is and the potential for new customer value, I would say lots. And you know this too, because I’ve used the example of other companies that have really gone after the problems that you said, versus selling the products they want to have. Like them or not, Tesla really isn’t a product seller. There is a thing called the Tesla, and it’s got different models. But the problem it solved was this sense that some people had about being electric, not petrol – that might have been a preference. Also, I don’t want to go to a dealer to buy a car, and I’d not like to go to the dealer to get service either. Downloadable software while it’s sitting in my driveway charging – that sounds pretty good. It’s the complex of those needs I have that they were able to capitalize on to create this extraordinary value. 

Paul 

It is interesting because, to your point, drawing the parallel, it’s in a way, Tesla, as an example, has solved multiple problems at once, broken through the entire value chain all the way from the dealer to the car manufacturer, to now even the entire ride-sharing industry as well. 

Rick  

100% absolutely. By the way, Paul, just to tap on that, the value chain is a construct of a supply-side world that says this is the way I built a product and I get it to market. Demand chain disrupts all that, because it’s how I think and want. And that’s what you just described that Tesla did. As a result, look at all this disruption. 

Paul 

Building on this, and thinking about our insurer friends, in a way, there is a very interesting parallel here. Retirement is one thing, financial wellness, financial security, not only for one’s financial wellness, but for one’s entire family. The way the industry has solved this for a huge amount of time has been more product selling than problem solving. Even in cases where it was problem solving, it was more of “let me solve that one sliver of the problem, versus all these things. I’ll go back to something I was saying earlier that AI is moving so quickly, and I’m being very cautious because I don’t want to make it sound like it’s this magical solution. It’s very complex.

One of the questions, for example, is whether these things are so complex that we would need a human in the interaction? Maybe. For the time being, that is probably the case. But even if that’s the case, the way humans are engaging with a customer, the breadth of the needs that they’re able to understand of the individual customers and their family, whether it is a point in time or over decades, and obviously, the breadth of solutions that they can provide and hyper-personalize and customize. I think there is a radical shift here that is in the process of happening. 

Rick  

And I would say it’s happening at much lower costs. So much more accessible and affordable. I can actually start with customer value work back and do it more efficiently and effectively with a greater cycle time. 

I wanted to make sure that I completed a thought, which I didn’t, because I got excited about only one part of my answer to your prior question. I do think that there’s also this adage of never confusing a clear view for a short distance. I think what you just talked about, family and financial wellness, triggered by life events through a period of time, is potentially a point of arrival or destination that says I’m going to do more of that. I’m going to do it with maybe more of this available smart that exists in the fabric of the world. Now, what is the set of experiments? How do I test my way to get to that different future?  

I think this is where, in picking up the cycle time of change, we talked about things that are enduring and then things that are really changing. I think the best path to dealing with uncertainty and volatility in the environment is to stare it in the face and say, I have a hypothesis. It’s a belief about how things are heading. Now I could be wrong, but I’m going to be in the game and actively engaged in learning as I go. I’m going to learn as fast as I can, because the faster I learn, the better off I’ll be. That agility is hypercritical as the world changes fast. The ability to then not only meet and master it but master it for your own hypothesis about where you’re heading and why you should be winning in that future. 

Paul 

Diving into this, I would love to get into your playbook for what this looks like. I think you’re calling it “AI trifecta”. What does this look like?  

I’m also reflecting before we shift to that – what I find interesting is, again, I was talking about the iPhone comparison. I’m old enough to remember when iPhone replaced Blackberry in corporations, and it was very much employee or individual pushed, which was: I have access to this, therefore, I don’t want to use these tiny keyboards. I want to have a richer interface. Interestingly, as a customer now, we’ve done some research around this. The majority of individuals nowadays are using AI for some form of financial advice. Now, is it the full picture? Is it fully regulatory compliant in terms of the type of answers you get? Is it as sturdy as a proper and well-accredited financial advisor will provide you with? Probably not, but it is priming the pump for, to your point, what it can look like. Also, it has a very different cost structure. It’s a very different cycle time. It’s another shift. That’s customer-led basically. 

Rick 

You’re correct. There’s tremendous uptake. One thing you and I have learned together, on some prior work we’ve done, is that money is emotional. That has lots of implications, including I don’t want to be embarrassed by what I don’t know. Where I think AI engagement around money matters is interesting is that AI is not a judge; it doesn’t judge me. If there are a lot of things I don’t know, it’s not telling me "you idiot, you should have known all these things". I can be private in my ignorance and potentially close that gap. Financial literacy continues to be an incredibly pressing problem. I can see some advantages. I think the dark side of that, though, is if you’re not good at prompt engineering, what do you do with it? I think there’s a lot to be said for domain-specific advice and guidance. 

Paul 

There are an insane number of opportunities for incumbents to take on that challenge and offer something that is a lot more valuable. How do you see the big questions that incumbents need to think about as they think about AI-led customer transformation? 

Rick  

I think that in times of great change, if we don’t have a plan, don’t be surprised if you show up underwhelming. I think having this chat with you about the whole creation of robotics, for example, in China – I am fascinated, I’m just a student, I’m a learner. What’s fascinating to me about that plan that created the robotics industry, particularly around manufacturing, is it was a very long view of how things might develop, including how cultural shifts would occur and what jobs people might and might not want, what that would mean for a workforce on a manufacturing assembly line versus not. It wasn’t just that it’s been an extraordinary innovation, but it was planned thoughtfully. 

I think one of the most important things to do in times of real change is to have a view about where the puck is heading and its course and speed. Take a position. It doesn’t mean that you’re going to be right. This is interesting – it’s not the illusion of infallibility or that you have a crystal ball, but for this notion of collision of megatrends, the megatrends actually already are observable, and so the ideas play them forward. Be thoughtful and rigorous in saying, what do we think is going to happen in 2030 based on what is already observable? Let me stand there and look back to the present and understand what crown jewels I really have? What differentiates me? What am I doing that could eventually be a crown jewel? Should I accelerate it or not? But stand in the future, look back and then say if I’m heading into that 5-year horizon with some velocity, with some competitive separation, what would I need to do over the next 18 months, and does my current plan or record position me to be doing those things?  

If not, I'd better start to challenge it and shape it. I think the number one play is to do that, I think it is so important. And again, not to pretend to be right, but the leadership team is aligned and saying the same thing with the same words that have the same meaning. 

Paul 

As you figure out where to grow and where the puck is headed, there is an element of being clear about what trends we’re going to see. Potentially, what’s also going to become extinct. If you are, for example, surveying the populations that are in their 20s and 30s, but the population is structurally getting older, then you can see your own market suddenly dwindling, and at the same time, there are greater needs in the longevity space. That’s why I liked your example of robotics. Given the policies and everything in China, we could see the manufacturing workforce dwindling over time, so it has almost become a necessity to work on robotics. 

Rick 

If you decide that you’re going to compete and be differentiated, then this is a thing. A bet that you really have to place. We like to say: make an asymmetrical bet about that. Others either cannot do or will not do, which certainly happened in that case. 

Paul  

I want to pressure test this with you. There is an element of where you are going to play, and therefore, how you are going to further build your competitive modes. Potentially starting to think about what’s likely going to become over time, either deprioritized or commoditized. 

Rick 

No longer part of the future? I’m glad you brought that up, Paul, because I think that’s probably the most difficult thing to do. When you do that, “play it forward and let me see if I am heading on the right path and the right speed,” it is to look at the portfolio businesses and say some of the things that took us to our present are just simply not going to be a big part of our future.  

This is my learning about the Microsoft experience – that desktop office was simply not going to be part of the future. It just didn’t give us any insight into what humans really wanted to do, so we said we'd better let that go, put on life support, and race to build Office 365. I think every company has these moments, they call them “cash cows,” or they’ll use whatever words they use, but they know what things they’ve been hugging that have been big but are no longer growing and are not part of the future trajectory. I think being honest and then saying I’m going to open my eyes and clinically and dispassionately manage it into obsolescence, maybe even divest it, because I’ve got to let it go that fast. I think that is one of the most important decisions, because unless and until you do that, it’s hard to fund the future. You can’t carry forward a cost structure where you keep ending everything like that. You have to be able to fund the future. 

Paul 

One of the big challenges that you and I have spent a lot of time discussing is: it’s not even just dollars; it’s also management attention. 

Rick 

The hardest and the scarcest of all. That’s exactly right.

Paul 

And how it is extremely easy to overallocate management attention to what you call “productivity zone” or “cash cows,” while underallocating what could be the bets for the future that are not quite yet at the scale that you need, but deserve that attention and funding at the same time. 

Rick 

Now you’re getting at the management discipline that it takes: continuing to honor stakeholder commitments in the present, downshifting from things that are going to take me to the promised land, and developing a muscle about systematic test-and-learn.  

This is why I’m such a believer in this four-zone notion. The performance zone is BAU. The productivity zone is “I’m going to manage things into obsolescence, make things extraordinarily efficient and the best”. Then the incubation and transformation zones are where I’m going to place bets about reinvention and/or growth, but probably in a portfolio of 10 bets, probably six or seven of those should be on reinvention, and maybe a couple on growth. Then I’m going to push one and only one bet at a time to materiality, because I don’t want to find myself in this place where I’m trying to push two or three things that get mid-size, but never quite break out and get escape velocity.  

Let’s get everybody focusing on making a thing material. And if we can do that, then let’s do two. Once I do one, let’s do two. I think that notion that all those zones take the right management attention, to your point, each of those zones has unique metrics. Each of those zones requires a certain temperament of a leader. If you don’t have great optimizers who are managing the productivity zone, don’t be surprised if it’s very difficult for the applied innovators and deployers to be successful. It’s because you’re asking them to do things that are simply unnatural and not possible. I think honoring all of those management archetypes and really having the right metrics zone by zone is so critical. 

That’s a new thing. For many companies. It’s not necessarily so new in tech. This is why I have a certain passion, having seen it in tech. In the tech sector, you’re rewarded for growth. You’re rewarded to go find the next big growth opportunity, where that’s not necessarily been the case in insurance. I think building the muscle that says it’s about low growth to high growth categories, and I’m going to actually start to do both things and be an expert. I think that is an interesting and important challenge, but an essential one when the world is changing quickly. 

Paul 

Building on this, we talked about where to grow, where the puck is headed, and therefore where you want to go. As we go into where to play, I’m going to set you up here a little bit. I know you like to talk about demand aggregators, ecosystem orchestrators, and component suppliers. If I look at insurers, they’ve typically been more of a component supplier in a broader ecosystem, sometimes in their own ecosystem if they had the front door, sometimes in somebody else’s.  

Things are evolving. We just talked about this – how to think about where to play. My inherent bias from the outset is that being a component supplier may not be the right place to be, especially if it’s almost a default decision. There might be some elements where you actually choose to be a component supplier that has these advantages and has a very clear view of how the broader ecosystem is playing. But I’m curious, where do you think the opportunities are, and what advice would you have for insurers? 

Rick 

I do think that where to play is so critically important. I do believe that there are these three [power positions]. We can give them whatever words we want, but there’s this demand aggregator notion of I am going to solve problems for Paul. Whatever Paul’s problems are, I’m going to solve them. I’m going to do it in an increasingly intimate, personalized, AI-powered way. That doesn’t mean I have to own the ecosystem or even orchestrate it, but I’m going to be that front door. Front door is not even a good way of thinking about it, but it’s almost the persona you go to around a set of needs, in this case, financial wellness. This notion of where to play is important, sector by sector or demand space by demand space. You don’t expect that the demand aggregator for medical purposes is going to be the same as your [medical service provider].  

That’s one, then there is the component supplier. You made a really important point, which is that defaulting to that is not a good decision. I’ll come back to it in a second. There’s a third place, which I think is really interesting, which is the ecosystem orchestrator. My job is to begin to get the hyper-scalers, the cloud, the fires, or the vertical solution players together to actually push a solution into the demand aggregator. And I’m going to source the components from component suppliers in an incredibly efficient and modern way. 

These three places – demand aggregator, ecosystem orchestrator, and component supplier – you can make money in all three of these. But they are an explicit choice, and there are very different skillsets across them. For example, that ecosystem orchestrator, in a lot of conversations with companies that think of that as a path to value, it often takes – I hate to call it “biz dev” because it seems to make it so pedestrian – the ability to actively engineer these relationships. If it’s going to be API-able, figure out what that is from a business standpoint before you go to the technology. What I mean by that is what are the give/gets, are those give/gets reasonable, and are there adequate decision rights? These are gnarly governance questions around that. That becomes incredibly important in differentiating skill and capability. Then the component supplier. If you’re trying to be a component supplier and you feel like your product can go into multiple ecosystems and serve many demand aggregators. That’s awesome. Think about monetizing. That’s great, but then should you have direct sales? Should you also work hard to own the distribution? Is that a sensible thing to do when you really need to make sure that your product is unbeatable and unmatched in terms of its economics and its ability to plug in and all these other things? I think being very clear about those, and making explicit choices on a business-by-business basis, is going to be critically important, especially in the age of AI. 

Paul 

It’s interesting. Just to take a couple of examples, it’s not about, can you do one without the other? It’s more about management attention, focus, and the capabilities needed to build; it takes a lot of effort. Being a component supplier is not an unrealistic place to be, but being able to say, I’m going to upgrade my insurance products once a year, I’m going to just make sure I have the right economics, I have the right investment solutions behind us – that is not enough anymore. You want to be able to hyper-personalize individual customers of different customer personas or archetypes.  

Even if you’re a component supplier, in insurance and financial services, the product could be more. It could be the insurance product, the economic promise to the customer, but also the digital engagement that comes with this or a series of services. We’re talking about retirement. That’s where you can start linking a lot of different things. That is something that, for the majority of companies, is going to require a massive shift in the operating model. Back to your point – are you committed to this, and are you committed to building all the right capabilities to build those competitive modes so that you do not get commoditized? 

Rick 

That’s right. As you decide where to play business by business, really think from the customer archetype – the family unit contemplating retirement and sandwich generation issues. Work back from that and say, what would the set of solutions need? Can I source some of those pieces from the ecosystem using agentic orchestration, as opposed to having to do everything myself? Does that liberate me to be excellent at the products where I am truly differentiated to the point of competitive mode? Let me light the way to the core shared capabilities that should be present and only do those and/or reengineer their rebuild or reinvent those in modern technology, as opposed to dealing with all of the tech debt that I might have. Use that proposition and what we know customers want to pay for to show the way to how I’m going to go about delivering against it. It’s thinking about the operating model, yes, but outside in and using that as a lens to figure out what is, in fact, needs to be modernized, and how to modernize it. This is where I think the notion of new value, plus efficiency and cycle time improvement. You can get both. It’s not an “either/or” but both ends done properly. 

Paul 

If I look back to the last couple of years, a lot of players in insurance and financial services and beyond looked at AI, and I feel like, oftentimes, it was more of “on the fringe” or a tech thing. While the way we’re talking about this here is – you need to start from the business problem and the customer problem. There is a very active choice to be made about how you are going to be using AI to accelerate the build of your new capabilities. And to your point, it’s both ends – cost and growth. 

I’m going to go back to my component supplier example. To me, using AI should be in service of “we have decided that we want to be a component supplier that’s going to be providing the best solution that is tailored to the exact need of each person, given their situation, their family needs, and where they’ve been and where they want to go on their financial roadmap, and even on their non-financial roadmap as it’s not about just financial needs. Therefore, everything we want to do is to better understand all these needs and tailor them. Therefore, any AI investment we make is in support of that. And it’s not a once-and-done thing. 

Rick 

I want to pause on it or underscore it, because right there lies all the difference in value from AI or insulating from the turbulence around AI. If I stared at AI and said, what could I do with it? You wouldn’t do what you just described. If you started with a solution, say, how do I make it better? How do I make it unmatched? By the way, there are three more vertical LLMs and other new goals that no one has thought about. But I can adapt and adopt it to do more. Then I should do that. It diminishes this fast evolution of the tech and says I’m putting it in the service of doing more for the customer.  

That’s my job. My job isn’t tracking the tech. My job is doing more for the customer, and it makes things clear and decision-making more focused when you adopt that logic. 

Paul 

Playing back your trifecta, how do we build our entire business model and our operations around this? In two points, it’s cost and growth. And how do we continuously evolve this? It’s not a one-time injection of AI or tech. How do we completely reinvent the way we operate? 

Rick 

Paul, we would be totally remiss if we didn’t talk about humans. What I mean by that is there’s this important muscle that you’ve just articulated. I want to draw it out and underscore, which is this muscle of rapid course correction and adaptation. This is not a leadership trait or a muscle that is well understood and activated in most incumbent organizations. Most incumbent organizations are rewarded for sustaining the mode, not finding the new mode. For this rapid course correction, doing it in a way that humans can sustain the change, understanding that if you’re going to move an organism from its old way to a new way, it’s going to take a lot of nudging. You can’t whack at it and hope to get it to the new state. You’re going to have to be able to say, okay, now you’ve started to collaborate cross-functionally, cross product, focused on an outcome. That’s great, but now how do we set the next OKRs, and what do we do to shift incentives to promote more of what you’re doing that leads you to a better future? 

Again, an example from my Microsoft experience, I thought it was fascinating to see when and how, in sequence, shifting the incentive system had so much to do with promoting greater collaboration across the organization, which was critically important to showing up as “One Microsoft”, which was the watchword. But it was all in time. Going straight to incentives isn’t the answer. Standing up the right apparatus – I call it an accelerator – to test and learn across all management dimensions, technology, AI, and thinking through the lens of the customer. These things require different behaviors and spaces in which people can learn quickly.  

Every company’s model for how they get to the future is going to be different, because it’ll be culturally appropriate. There’s no one-size-fits-all there, but I just wanted to underscore that we would be really remiss if we didn’t call out the importance of change and approaches to change. Which I think is different. In other words, you have to change the way you change to move into this AI future that we’re talking about. 

Paul 

That’s fascinating, and I would like to again reference the four zones where every zone requires different metrics for success, different leaders, and just different motions, in general. Maybe shifting to our third act here on “what ifs” and big bets. Thinking about our insurance and broader financial wellness space, if you fast-forward a few years, what’s your view on what will feel radically different? Feel free to go either in terms of how insurers would serve their customers or how customers would also engage. What are your big bets for the next few years? 

Rick 

Paul, this is a tough one for me, because for so long, I’ve lived in this world of looking at many of these gnarly problems that are underserved in insurance. There is this challenge of historically being able to really play the balance sheet and to really make this be about safeguarding the future.  

However, if I’m going to be a financial wellness provider, it means that I’m a very different-looking company than the insurers of today. I think of really difficult decisions around: how do I save for a rainy day, how do I reduce my debt, how do I begin to think of placing bets on my future retirement? If I’m heading to that age, I care a lot more about that. If I’m early in my career, I’m probably thinking more about a home and a family. Understanding those things that, to me, are a holistic financial security proposition. Having a company break out and redefine the category is what I’m really excited about. I’m always excited about – is there a way to redefine the category you’re in? I don’t see any reason to stop that or prevent that. AI can be a great vehicle for redefining the category you’re in and unleashing a whole next wave of growth along the way. I would love to see that happen. 

Paul 

There are some of these big problems that we’ve been talking about for quite a while. Retirement is bound to become a greater problem. People are living longer. The birth rates are declining. People have more dependence. The problem is there, and it’s not a problem that is just changing overnight. It has been building up for a long time.  

When looking at insurance and the broader financial services industry, there is almost the notion that insurers are somewhat safe, because it’s difficult even for big tech to replicate what it’s doing. But if you push forward what you are saying about demand aggregator, ecosystem orchestrator, and component supplier, there is a risk for the insurance industry to get commoditized to just being a capital provider. Somebody else is busting up the value chain, reorienting around the customer needs, and taking the lion’s share of the profit and the attention from the customer while getting supply from an industry that’s dwindling and dwindling. 

Rick 

Paul, we’ve seen some signs of this already. If you think of some of the big captives in the world that are powering growth in problem-solving in new spaces. Amazon has bought One Medical. That’s interesting. That’s not e-commerce, that’s not even selling cloud services or workloads on the cloud. You’re starting to see movement toward knitting together solutions for different ecosystems and different sets of customer needs. If the demand migrates to solving problems, then the notion of insurance and risk management is tied to that: what does an insurer do to participate in a world where that attention is moving to different ways of engagement powered by different data sets?  

I think this is something critically important. I do think the pace with which that engagement has migrated and how fast it can accelerate in the AI world is very real. From an old marketer’s perspective, again putting back on the adtech hat, we used to think about strong and weak signals and then building a signal factory to figure out a customer’s intent. That’s what we were trying to do. A strong signal is the search query. A weaker signal is the time you spent on the engaged web or dwell time on a website. We try to infer from that your intent. Inside this substrate of chat is all my intent, and my intent with memory. This is important to me to understand it for what it is. To figure out how I need to be present in that substrate to be increasingly relevant for higher-order problems. Again, not sky is falling, but boy, don’t wait. I think it’s somewhere between there. 

Paul 

If I look at the next 12 or 18 months, maybe even the next six months, what are the big shifts that you anticipate? What are we going to be seeing a lot more of, and what would you say executives should get ready for? 

Rick 

Having lived through waves of technology – and certainly I learned this in the dotcom bomb era – big things and big ships don’t really become big unless there’s enterprise monetization. I tend to focus my attention on players like Anthropic or Gemini, not because I like them or I’m saying they’re going to win, but because I think they’re really focused on solving enterprise problems. 

I think the enterprise has mostly been learning. I was going to say dabbling, but that would be wrong. I think giving tools, getting people acculturated and figuring out what we can do with Copilot. I think it’s so important to be aware of what’s possible for me in this world. There’s something about the end-to-end workflows, how those could look and could get AI-powered and what the outcomes would be, if I did that holistically end to end. I think of that more as a reimagining or a reinvention of a challenge. I’m hearing and sensing more of “Yes, let’s take that on.” That will be critical for unleashing value, because it means that what’s on the other side of the rainbow is humans who are then amplified or augmented in some new workstream. That may be inside the enterprise and outside the enterprise for activity streams. That is what they’re going to get to: not replacing people, but having people doing very different work, augmented, amplified, and enabled. I think we are barely there. We’re just scratching the surface and what that can be. I think looking forward, I would expect that we’ll see much more truly digitized and algorithm-driven enterprise, and enterprise monetization. 

Paul  

One thing we didn’t really talk about in the last hour is that AI is just for cutting jobs, which oftentimes tends to be the shortcut. It’s more about how you augment humans. But that also means if you want to be the human who’s augmented and enabled, your job description might be completely different tomorrow than it is today. There is a transformation. You were saying, let’s keep the human in the conversation. 

Rick  

The skillset has to evolve. There’s no question. Back to the point about an accelerator model and the building of the new muscle. It’s not just about learning the skills. It’s about applying them, trying them on, and marinating in them to test and learn. Last I checked, the pace of adoption is as fast as humans can adopt. How fast can humans adapt and adopt? I think faster, but I think ways of working inside of enterprises have been particularly difficult to change. How do we unleash people who now have a sense because of their chat interactions at home and on the go? How do they begin to think about imagining a very different workplace, and can that allow them to go from the back foot to the front foot? 

I was in some discussions with treasury functions. On one hand, being highly regulated and used to having to do so much work to just make sure everything is spot on, as opposed to: I can be a risk adviser and be on my feet to understand what the balance sheet effects might be of some geopolitical development. That’s a very interesting thing, because it creates truly interesting work and a role that is currently impossible for a whole range of reasons. Anyway, I think that notion of back foot and front foot and new work is quite exciting, but I think we’re going to have to invent our way there. It’s going to be difficult and hard work. 

Paul 

Maybe just to close – would love to get your final words of wisdom. As you think about the AI revolution playing out, what advice would you have for insurance executives? What words of wisdom would you leave them with? 

Rick 

Maybe I’ll say three things. First, figure out how to be both bold and provocative and incredibly pragmatic at the same time. The example I often give is when I was doing the startup thing, your venture investors want you to walk in the door and pound the table on how you see a new category, and you’re going to be the category killer. Then they go tell all their other venture investors over lunch. You have to be incredibly capital efficient, like the proceeds of your money come Monday morning are going to be gone. So that bold and pragmatic thing is a very difficult thing to do, because it’s going to take both. 

Second is to be really aligned, and we talked about this earlier, that the leadership team sees the future, not to say that they got it right, but they should see it the same way. They are clear-headed about how fast they need to move with the risks. That is going to be incredibly important. 

The third thing I’d say is, over many years, we’ve allowed the strategy and direction setting to live in one place, and the operating model and operationalizing is somebody else’s responsibility. It’s going to be important to keep all these things in lockstep and have a very compelling narrative, both externally to investors, which would also be a change narrative, and a way of mobilizing people internally. Those would be my three big hopes and wishes. 

Paul  

Rick, thank you so much for your time. It was such a pleasure having you with us. 

Rick  

It’s always great to be with you, Paul. Thank you so much. 

Paul 

That was Rick Chavez, partner and Customer First leader at Oliver Wyman. I am Paul Ricard. Thanks for listening, and I’ll see you next time. 

This transcript has been edited for clarity. 

Oliver Wyman Partner and Leader of Customer First, Rick Chavez, is an innovator with two decades’ experience at the forefront of the digital revolution. His experience spans a wide range of organizations — from pure start-up ventures through to $80 billion global corporations — as senior executive, advisor and Board member.

Rick focuses on helping senior leaders unlock the potential of this next wave of AI-triggered disruption to drive customer value and investor enthusiasm. He has significant expertise applying proven methods for “dealing with disruption” – pressure-tested in the tech sector – to the challenges of growth and reinvention for executives in banking, insurance and technology. He led the design and launch of new entities to harness disruptive forces: a NewCo for a major US life insurer and a multi-billion-dollar NewDiv for a leading mobile carrier. 

Rick collaborates closely with industry thought leader Geoffrey Moore, with his commercialized management models for growth and innovation  forming the basis of case studies in Moore’s recent books, Escape Velocity and Zone to Win, which serve as essential playbooks for digital innovators in the tech sector and beyond. He has authored unique points of view and was a frequent keynote speaker at major industry events such as MomentumAI Finance conference, TedX, AdWeek, Ad:Tech, ARF Re:Think, ProXXima, and Cannes Lions.

Oliver Wyman Partner and Head of Asia Pacific Insurance and Asset Management, Paul Ricard is based in Singapore. Paul works closely with businesses to reinvent their strategies, products, and services — and to fuel top-line growth opportunities.

He works with clients across Asia Pacific, as well as the Americas and Europe. He regularly partners with firms to reinvent their business strategy, rethink their priorities, and to modernize their technology while accounting for rapidly changing customer needs. He understands his clients’ realities, and thrives on helping them innovate and strengthen relationships with their customers while factoring existing challenges.

The insurance industry is under intense pressure to reinvent itself as rising customer expectations and rapid advances in AI redefine how value is created.  

In this episode of Reinventing Insurance, Rick Chavez, Oliver Wyman partner and leader of CustomerFirst, talks about putting customers at the center of AI‑enabled reinvention. Drawing on his experience leading large-scale technology transformations and innovation, Rick explains why insurers should start at the endpoint of the demand chain, take explicit positions on where to play, and reallocate management attention across four operating zones: performance, productivity, transformation, and incubation.  

The conversation walks through the “AI trifecta” for customer value, the trade-offs between being a demand aggregator, an ecosystem orchestrator, or a component supplier, and how AI can make personalized financial wellness and retirement solutions more accessible and affordable. 

Key topics include:

• Prioritizing which business areas to modernize, which to manage into obsolescence, and where to place one material bet at a time. 
• How to design operating models, incentives, and accelerators to test, learn, and scale AI‑driven customer propositions. 
• Practical thinking on demand aggregation, ecosystem orchestration, and building component products that plug into broader customer solutions. 

This episode is part of our Reinventing Insurance series, a series that explores best practices for taking a CustomerFirst approach to innovation within Insurance. Throughout this series, host Paul Ricard discusses lessons, challenges, and new ways of working with guests who will share their first-hand experiences.

Subscribe for more on: Apple Podcasts | Spotify 

Putting customers first as AI reshapes the insurance future

Paul Ricard 

Welcome to Reinventing Insurance. Today, I have the pleasure of welcoming Rick Chavez, partner and leader of CustomerFirst at Oliver Wyman. Welcome, Rick. 

Rick Chavez 

Thank you, Paul. It’s great to be with you. 

Paul 

Rick, you’re not foreign to the Reinventing Insurance Podcast. I think you recorded an episode with my colleague, Mick Maloney, a little while ago. 

Rick 

That was fun. 

Paul  

We’re going to look to top that today. For those who haven’t listened to it, Rick previously talked about customer-led reinvention, his experience with the Microsoft transformation from the inside, and many other themes. We’ll have a few callbacks to these as we talk today, but our focus is going to be about being customer-first in the age of AI and where insurance goes next. Before we unravel what we’re about to discuss today, we’d love for you to briefly tell us about yourself, Rick. 

Rick 

The place we’re in now is so fascinating to me. I dabbled in what was then called an ARPAnet – now called the internet – before it was even a commercial phenomenon. If you can imagine, I’m that old. I was also dabbling with early AI, and that is another one of these curiosities, because a lot of the algorithmic innovation that we are able to enjoy now, in terms of its activation and applicability, was actually pushed hard in the 80s, but it was back in a time when we were so completely wrong about how to use it. Our theory about using these algorithms for good was not wrong; it was simply at the wrong time. Watching things evolve through the years and seeing the evolution of technology has first sobered me, and still broadly encouraged me and made me an optimist. And I’m still an optimist, Paul. It’s sometimes hard to maintain optimism, but I’m still a glass-half-full kind of person. 

In terms of my story, I stumbled into management consulting out of college. I found that I was reasonably good at it, and I liked it. What was the most interesting thing about it, for me, was that it was a great vantage point to see things in the world that you want to fix, or that you think just don’t make sense. So, I jumped out, did a startup, sold that, then went back to consulting to detox. Found another idea, jumped out and built a company at a time I call ”the great happiness internet 1.0”. All boats are rising. It was actually not a time I predicted. I was just building a great company that was hopefully going to do great things. Then the dotcom bomb was quite painful at the time, but incredibly informative, like an incredibly important learning experience for me. I took some of the ideas that I just couldn’t let go of, and they stuck with me as I went west.  

I was on the East Coast for a long time building the startups. I went west and got to work very closely with Jeff Moore (Geoffrey A. Moore), who many people know is the guy who wrote “Crossing the Chasm”, and is often thought of as the father of innovation. He is very well known on the West Coast and tech companies, but completely unknown on the East Coast. We both got very interested around the same time in innovation at scale – me from having been a startup fellow, and Jeff from having been a venture investor. We were interested not in the challenge of being a startup, when you’re being incentivized and pushed to grow with no existing stakeholder commitments. That’s what startups are.  

What happens when you’re Cisco or SAP or Yahoo or Adobe, which were clients, where the company has grown to a place, and then growth has stalled out? How do you reignite the engines of growth? I tell you that because that passion or that interest became a passion, and it stuck with me to the present. It took me through two tours of duty, one at Adobe launching what was then called Customer Experience Management and morphed into the Marketing Cloud Business of today, which is amazing. Then, as you mentioned, I was part of the transformation effort at Microsoft as Steve Ballmer handed the keys to Satya (Nadella, CEO of Microsoft). I got there by having friends at Yahoo who had reported themselves as the search team at Microsoft. 

I brought that thinking about dealing with disruption and living through transformation to my work at Oliver Wyman. CustomerFirst, to me, is really all about dealing with disruption, with a very strong view that if you start at the endpoint of a demand chain, where people are either in a workflow or at home or on the go, have big pressing problems to be solved, which could be solved better with a digital experience powered by data. That essential thesis of dealing with disruption, by looking at customers’ problems, I would argue has been a passion pre-Oliver Wyman, but certainly has been a passion as I’ve been here. 

Paul  

You’re basically threading the needle with what we’re about to discuss. You’re helping large incumbents dealing with disruption and with innovation at scale, which I think you’re starting to allude to – there is a method to the madness. 

Rick 

There is a method to the madness. I do like to say that the best entrepreneurs, the best innovators, are the most disciplined people you’ll meet. It seems to be a conundrum because I think many people who work in innovation think that this is fun. Truthfully, if you’re doing it in its truest form, it probably hurts. And that’s probably just about right, because it should be a very systematic, thoughtful test-and-learn discipline approach. I think the doing of it, and doing it right, is critically important and is something a lot of our clients are still developing and working on. 

Paul 

It’s not just the free soft drinks and the sneakers in the open space. It certainly seems like there are a lot of tectonic shifts that are happening. I know you like to talk about the collision of megatrends, and it feels like this is something that is continuing to happen and accelerate. Can you tell us a little bit what’s happening and what feels different? 

Rick 

Let me start by first saying some of what’s happening now was predictable. Any disruption, if it truly is a disruption – and you mentioned this is a collision of megatrends – that needs shifts in behavior, along with maybe societal, political, and regulatory things that are happening. Technology, I like to think of it more as a tailwind as opposed to the main event. The reason is that if you stare at technology as is the case right now in this AI moment, no matter what we say about what will be three months from now, we would be completely wrong. 

If you look at that collision and you say, all right, what is enduring about humans in their work and their attitudes and approaches to digital technology that either allows more of what they want, and less of what they don’t want to be part of their lives. I would say, first of all, that’s enduring. I’m going to come back to that. Second, that’s what’s so radically different about now versus then. We’ve never had as much digital familiarity. If you think about it, you have extraordinary familiarity with all things digital. We carry around supercomputers in our pockets. They’re connected as if they’re another finger and appendage. 

The second thing is connectivity. Pervasive connectivity. If you think about what’s happened in evolution after evolution, we have 5G, we have fiber. These things really, really matter because it means that those edge devices can do more, and they can do more that then help us be more. You have this context of pervasive connectivity that allows for very rich experiences, which we expect, and we actually want them to be intelligent. I will assert that most of the experiences have not been intelligent. Most of what we say about smartphones is, frankly, more dumb than smart. I’m sorry to say that. But the reason I say that, now that intelligence can be pushed out in the AI economy, you have people hungry for that thing and having expected it already. So that’s why this meteoric adoption of all things chat, whether it’s OpenAI or Claude or Gemini or OpenClaw, why does it look like it's instant? I think it’s because people have been expecting this kind of engagement with the world for a very long time. 

Think about it this way. You and I have been taught to use a keyboard. We’ve been taught to use our thumbs [for smartphone keyboards]. Neither of those things is particularly human. We’re okay with them, but they’re not particularly human. In this world, what’s showing up is the other thing that’s happening with adoption, making it human and natural, like the interface is my voice. This, too, is such a stunning thing because in 2001 or 2002, I was CEO of the first multimodal company that invented multimodal. We thought then, too, that it was going to get dispersed quickly. Think about how long it took. It’s this NLP natural language interaction model with deep intelligence embedded in the fabric of the world, and its ability to be dispersed and then onboarded into our lives is completely different. That is a phenomenon that is unique to this moment. 

Paul 

You are saying that it’s so enduring, and people are experiencing this at scale in their day-to-day lives. What is interesting is that there is an expectation that if a company is going to engage with me, either to solve my problem, to sell me something, or to interact with me, it’s going to feel the same way these things have felt. I would love your take on this. It feels very similar, for example, to the iPhone moment when the iPhone came out. Now, suddenly, if a company is not engaging with someone through an app, you are dead on arrival. The web 1.0 interface was… 

Rick 

became the mobile app. Exactly. That’s 100%. 

Paul 

That’s one thing. At the same time – and I would love your take on this – what is also interesting is that the pace of change is so rapid that if you got used to something two months ago, it is very, very different now. I’m also linking this to the expectation you would have from corporate, where you need to get up with the program more and more quickly. 

Rick  

The cycle time changes. Let’s take these two things because there’s a conundrum in there. One is that some things are enduring, which is to say that they’re not changing, and what does that mean? Then there’s an enormous amount of change in the cycle time, which has never been faster. We have both these things at the same time. 

I think, first, let’s take the enduring one. I do believe that the big vexing problems in the world are largely still underserved. Let me put my marketer’s hat on. Let’s pretend I’m back in the adtech days that I came from. One of the nirvanas was – if Paul’s driving along home, and it’s been a long day, and he was expected to be the dinner preparer. There’s no way he is going to be able to do that in time. But I know that Paul takes a certain route and has a certain expectation. He’s a little late actually getting home. I wonder if I could surface an offer to him to stop at some really interesting place that has the cuisine that he can pick up at home. Would that feel like magic to you that it not only knows you and your habits, but that in fact you’re kind of anxious and a little bit upset at yourself that you’re getting home late. That is an example of intelligence serving you a thing that might make a lot of sense, that you can then wrap around that moment to do something you would otherwise not have been able to do. That is the solving of a problem. And that’s been a marketer’s nirvana for a very long time. 

I think there’s a whole range of problems like that. The new intelligence environment and the ambient intelligence should be unleashed. There are still a lot of these big problems that are not solved. Like we’ve talked about this a lot: how do I solve for retirement? In my case, it might be very complex. My spouse might have one idea. I might have another. We might have to think about our kids, maybe with the sandwich generation, there are all these different kinds of considerations. No one is exactly the same. There are patterns that may rhyme, but they’re not explicitly the same. If I look at that problem, I would say, Jeez, [I would love to have] some intelligence around nudging me in one direction or another, or alerting me, or even making it simple to have a unified view of my financials. These are nontrivial problems.  

So, if I look at what the undiscovered country is and the potential for new customer value, I would say lots. And you know this too, because I’ve used the example of other companies that have really gone after the problems that you said, versus selling the products they want to have. Like them or not, Tesla really isn’t a product seller. There is a thing called the Tesla, and it’s got different models. But the problem it solved was this sense that some people had about being electric, not petrol – that might have been a preference. Also, I don’t want to go to a dealer to buy a car, and I’d not like to go to the dealer to get service either. Downloadable software while it’s sitting in my driveway charging – that sounds pretty good. It’s the complex of those needs I have that they were able to capitalize on to create this extraordinary value. 

Paul 

It is interesting because, to your point, drawing the parallel, it’s in a way, Tesla, as an example, has solved multiple problems at once, broken through the entire value chain all the way from the dealer to the car manufacturer, to now even the entire ride-sharing industry as well. 

Rick  

100% absolutely. By the way, Paul, just to tap on that, the value chain is a construct of a supply-side world that says this is the way I built a product and I get it to market. Demand chain disrupts all that, because it’s how I think and want. And that’s what you just described that Tesla did. As a result, look at all this disruption. 

Paul 

Building on this, and thinking about our insurer friends, in a way, there is a very interesting parallel here. Retirement is one thing, financial wellness, financial security, not only for one’s financial wellness, but for one’s entire family. The way the industry has solved this for a huge amount of time has been more product selling than problem solving. Even in cases where it was problem solving, it was more of “let me solve that one sliver of the problem, versus all these things. I’ll go back to something I was saying earlier that AI is moving so quickly, and I’m being very cautious because I don’t want to make it sound like it’s this magical solution. It’s very complex.

One of the questions, for example, is whether these things are so complex that we would need a human in the interaction? Maybe. For the time being, that is probably the case. But even if that’s the case, the way humans are engaging with a customer, the breadth of the needs that they’re able to understand of the individual customers and their family, whether it is a point in time or over decades, and obviously, the breadth of solutions that they can provide and hyper-personalize and customize. I think there is a radical shift here that is in the process of happening. 

Rick  

And I would say it’s happening at much lower costs. So much more accessible and affordable. I can actually start with customer value work back and do it more efficiently and effectively with a greater cycle time. 

I wanted to make sure that I completed a thought, which I didn’t, because I got excited about only one part of my answer to your prior question. I do think that there’s also this adage of never confusing a clear view for a short distance. I think what you just talked about, family and financial wellness, triggered by life events through a period of time, is potentially a point of arrival or destination that says I’m going to do more of that. I’m going to do it with maybe more of this available smart that exists in the fabric of the world. Now, what is the set of experiments? How do I test my way to get to that different future?  

I think this is where, in picking up the cycle time of change, we talked about things that are enduring and then things that are really changing. I think the best path to dealing with uncertainty and volatility in the environment is to stare it in the face and say, I have a hypothesis. It’s a belief about how things are heading. Now I could be wrong, but I’m going to be in the game and actively engaged in learning as I go. I’m going to learn as fast as I can, because the faster I learn, the better off I’ll be. That agility is hypercritical as the world changes fast. The ability to then not only meet and master it but master it for your own hypothesis about where you’re heading and why you should be winning in that future. 

Paul 

Diving into this, I would love to get into your playbook for what this looks like. I think you’re calling it “AI trifecta”. What does this look like?  

I’m also reflecting before we shift to that – what I find interesting is, again, I was talking about the iPhone comparison. I’m old enough to remember when iPhone replaced Blackberry in corporations, and it was very much employee or individual pushed, which was: I have access to this, therefore, I don’t want to use these tiny keyboards. I want to have a richer interface. Interestingly, as a customer now, we’ve done some research around this. The majority of individuals nowadays are using AI for some form of financial advice. Now, is it the full picture? Is it fully regulatory compliant in terms of the type of answers you get? Is it as sturdy as a proper and well-accredited financial advisor will provide you with? Probably not, but it is priming the pump for, to your point, what it can look like. Also, it has a very different cost structure. It’s a very different cycle time. It’s another shift. That’s customer-led basically. 

Rick 

You’re correct. There’s tremendous uptake. One thing you and I have learned together, on some prior work we’ve done, is that money is emotional. That has lots of implications, including I don’t want to be embarrassed by what I don’t know. Where I think AI engagement around money matters is interesting is that AI is not a judge; it doesn’t judge me. If there are a lot of things I don’t know, it’s not telling me "you idiot, you should have known all these things". I can be private in my ignorance and potentially close that gap. Financial literacy continues to be an incredibly pressing problem. I can see some advantages. I think the dark side of that, though, is if you’re not good at prompt engineering, what do you do with it? I think there’s a lot to be said for domain-specific advice and guidance. 

Paul 

There are an insane number of opportunities for incumbents to take on that challenge and offer something that is a lot more valuable. How do you see the big questions that incumbents need to think about as they think about AI-led customer transformation? 

Rick  

I think that in times of great change, if we don’t have a plan, don’t be surprised if you show up underwhelming. I think having this chat with you about the whole creation of robotics, for example, in China – I am fascinated, I’m just a student, I’m a learner. What’s fascinating to me about that plan that created the robotics industry, particularly around manufacturing, is it was a very long view of how things might develop, including how cultural shifts would occur and what jobs people might and might not want, what that would mean for a workforce on a manufacturing assembly line versus not. It wasn’t just that it’s been an extraordinary innovation, but it was planned thoughtfully. 

I think one of the most important things to do in times of real change is to have a view about where the puck is heading and its course and speed. Take a position. It doesn’t mean that you’re going to be right. This is interesting – it’s not the illusion of infallibility or that you have a crystal ball, but for this notion of collision of megatrends, the megatrends actually already are observable, and so the ideas play them forward. Be thoughtful and rigorous in saying, what do we think is going to happen in 2030 based on what is already observable? Let me stand there and look back to the present and understand what crown jewels I really have? What differentiates me? What am I doing that could eventually be a crown jewel? Should I accelerate it or not? But stand in the future, look back and then say if I’m heading into that 5-year horizon with some velocity, with some competitive separation, what would I need to do over the next 18 months, and does my current plan or record position me to be doing those things?  

If not, I'd better start to challenge it and shape it. I think the number one play is to do that, I think it is so important. And again, not to pretend to be right, but the leadership team is aligned and saying the same thing with the same words that have the same meaning. 

Paul 

As you figure out where to grow and where the puck is headed, there is an element of being clear about what trends we’re going to see. Potentially, what’s also going to become extinct. If you are, for example, surveying the populations that are in their 20s and 30s, but the population is structurally getting older, then you can see your own market suddenly dwindling, and at the same time, there are greater needs in the longevity space. That’s why I liked your example of robotics. Given the policies and everything in China, we could see the manufacturing workforce dwindling over time, so it has almost become a necessity to work on robotics. 

Rick 

If you decide that you’re going to compete and be differentiated, then this is a thing. A bet that you really have to place. We like to say: make an asymmetrical bet about that. Others either cannot do or will not do, which certainly happened in that case. 

Paul  

I want to pressure test this with you. There is an element of where you are going to play, and therefore, how you are going to further build your competitive modes. Potentially starting to think about what’s likely going to become over time, either deprioritized or commoditized. 

Rick 

No longer part of the future? I’m glad you brought that up, Paul, because I think that’s probably the most difficult thing to do. When you do that, “play it forward and let me see if I am heading on the right path and the right speed,” it is to look at the portfolio businesses and say some of the things that took us to our present are just simply not going to be a big part of our future.  

This is my learning about the Microsoft experience – that desktop office was simply not going to be part of the future. It just didn’t give us any insight into what humans really wanted to do, so we said we'd better let that go, put on life support, and race to build Office 365. I think every company has these moments, they call them “cash cows,” or they’ll use whatever words they use, but they know what things they’ve been hugging that have been big but are no longer growing and are not part of the future trajectory. I think being honest and then saying I’m going to open my eyes and clinically and dispassionately manage it into obsolescence, maybe even divest it, because I’ve got to let it go that fast. I think that is one of the most important decisions, because unless and until you do that, it’s hard to fund the future. You can’t carry forward a cost structure where you keep ending everything like that. You have to be able to fund the future. 

Paul 

One of the big challenges that you and I have spent a lot of time discussing is: it’s not even just dollars; it’s also management attention. 

Rick 

The hardest and the scarcest of all. That’s exactly right.

Paul 

And how it is extremely easy to overallocate management attention to what you call “productivity zone” or “cash cows,” while underallocating what could be the bets for the future that are not quite yet at the scale that you need, but deserve that attention and funding at the same time. 

Rick 

Now you’re getting at the management discipline that it takes: continuing to honor stakeholder commitments in the present, downshifting from things that are going to take me to the promised land, and developing a muscle about systematic test-and-learn.  

This is why I’m such a believer in this four-zone notion. The performance zone is BAU. The productivity zone is “I’m going to manage things into obsolescence, make things extraordinarily efficient and the best”. Then the incubation and transformation zones are where I’m going to place bets about reinvention and/or growth, but probably in a portfolio of 10 bets, probably six or seven of those should be on reinvention, and maybe a couple on growth. Then I’m going to push one and only one bet at a time to materiality, because I don’t want to find myself in this place where I’m trying to push two or three things that get mid-size, but never quite break out and get escape velocity.  

Let’s get everybody focusing on making a thing material. And if we can do that, then let’s do two. Once I do one, let’s do two. I think that notion that all those zones take the right management attention, to your point, each of those zones has unique metrics. Each of those zones requires a certain temperament of a leader. If you don’t have great optimizers who are managing the productivity zone, don’t be surprised if it’s very difficult for the applied innovators and deployers to be successful. It’s because you’re asking them to do things that are simply unnatural and not possible. I think honoring all of those management archetypes and really having the right metrics zone by zone is so critical. 

That’s a new thing. For many companies. It’s not necessarily so new in tech. This is why I have a certain passion, having seen it in tech. In the tech sector, you’re rewarded for growth. You’re rewarded to go find the next big growth opportunity, where that’s not necessarily been the case in insurance. I think building the muscle that says it’s about low growth to high growth categories, and I’m going to actually start to do both things and be an expert. I think that is an interesting and important challenge, but an essential one when the world is changing quickly. 

Paul 

Building on this, we talked about where to grow, where the puck is headed, and therefore where you want to go. As we go into where to play, I’m going to set you up here a little bit. I know you like to talk about demand aggregators, ecosystem orchestrators, and component suppliers. If I look at insurers, they’ve typically been more of a component supplier in a broader ecosystem, sometimes in their own ecosystem if they had the front door, sometimes in somebody else’s.  

Things are evolving. We just talked about this – how to think about where to play. My inherent bias from the outset is that being a component supplier may not be the right place to be, especially if it’s almost a default decision. There might be some elements where you actually choose to be a component supplier that has these advantages and has a very clear view of how the broader ecosystem is playing. But I’m curious, where do you think the opportunities are, and what advice would you have for insurers? 

Rick 

I do think that where to play is so critically important. I do believe that there are these three [power positions]. We can give them whatever words we want, but there’s this demand aggregator notion of I am going to solve problems for Paul. Whatever Paul’s problems are, I’m going to solve them. I’m going to do it in an increasingly intimate, personalized, AI-powered way. That doesn’t mean I have to own the ecosystem or even orchestrate it, but I’m going to be that front door. Front door is not even a good way of thinking about it, but it’s almost the persona you go to around a set of needs, in this case, financial wellness. This notion of where to play is important, sector by sector or demand space by demand space. You don’t expect that the demand aggregator for medical purposes is going to be the same as your [medical service provider].  

That’s one, then there is the component supplier. You made a really important point, which is that defaulting to that is not a good decision. I’ll come back to it in a second. There’s a third place, which I think is really interesting, which is the ecosystem orchestrator. My job is to begin to get the hyper-scalers, the cloud, the fires, or the vertical solution players together to actually push a solution into the demand aggregator. And I’m going to source the components from component suppliers in an incredibly efficient and modern way. 

These three places – demand aggregator, ecosystem orchestrator, and component supplier – you can make money in all three of these. But they are an explicit choice, and there are very different skillsets across them. For example, that ecosystem orchestrator, in a lot of conversations with companies that think of that as a path to value, it often takes – I hate to call it “biz dev” because it seems to make it so pedestrian – the ability to actively engineer these relationships. If it’s going to be API-able, figure out what that is from a business standpoint before you go to the technology. What I mean by that is what are the give/gets, are those give/gets reasonable, and are there adequate decision rights? These are gnarly governance questions around that. That becomes incredibly important in differentiating skill and capability. Then the component supplier. If you’re trying to be a component supplier and you feel like your product can go into multiple ecosystems and serve many demand aggregators. That’s awesome. Think about monetizing. That’s great, but then should you have direct sales? Should you also work hard to own the distribution? Is that a sensible thing to do when you really need to make sure that your product is unbeatable and unmatched in terms of its economics and its ability to plug in and all these other things? I think being very clear about those, and making explicit choices on a business-by-business basis, is going to be critically important, especially in the age of AI. 

Paul 

It’s interesting. Just to take a couple of examples, it’s not about, can you do one without the other? It’s more about management attention, focus, and the capabilities needed to build; it takes a lot of effort. Being a component supplier is not an unrealistic place to be, but being able to say, I’m going to upgrade my insurance products once a year, I’m going to just make sure I have the right economics, I have the right investment solutions behind us – that is not enough anymore. You want to be able to hyper-personalize individual customers of different customer personas or archetypes.  

Even if you’re a component supplier, in insurance and financial services, the product could be more. It could be the insurance product, the economic promise to the customer, but also the digital engagement that comes with this or a series of services. We’re talking about retirement. That’s where you can start linking a lot of different things. That is something that, for the majority of companies, is going to require a massive shift in the operating model. Back to your point – are you committed to this, and are you committed to building all the right capabilities to build those competitive modes so that you do not get commoditized? 

Rick 

That’s right. As you decide where to play business by business, really think from the customer archetype – the family unit contemplating retirement and sandwich generation issues. Work back from that and say, what would the set of solutions need? Can I source some of those pieces from the ecosystem using agentic orchestration, as opposed to having to do everything myself? Does that liberate me to be excellent at the products where I am truly differentiated to the point of competitive mode? Let me light the way to the core shared capabilities that should be present and only do those and/or reengineer their rebuild or reinvent those in modern technology, as opposed to dealing with all of the tech debt that I might have. Use that proposition and what we know customers want to pay for to show the way to how I’m going to go about delivering against it. It’s thinking about the operating model, yes, but outside in and using that as a lens to figure out what is, in fact, needs to be modernized, and how to modernize it. This is where I think the notion of new value, plus efficiency and cycle time improvement. You can get both. It’s not an “either/or” but both ends done properly. 

Paul 

If I look back to the last couple of years, a lot of players in insurance and financial services and beyond looked at AI, and I feel like, oftentimes, it was more of “on the fringe” or a tech thing. While the way we’re talking about this here is – you need to start from the business problem and the customer problem. There is a very active choice to be made about how you are going to be using AI to accelerate the build of your new capabilities. And to your point, it’s both ends – cost and growth. 

I’m going to go back to my component supplier example. To me, using AI should be in service of “we have decided that we want to be a component supplier that’s going to be providing the best solution that is tailored to the exact need of each person, given their situation, their family needs, and where they’ve been and where they want to go on their financial roadmap, and even on their non-financial roadmap as it’s not about just financial needs. Therefore, everything we want to do is to better understand all these needs and tailor them. Therefore, any AI investment we make is in support of that. And it’s not a once-and-done thing. 

Rick 

I want to pause on it or underscore it, because right there lies all the difference in value from AI or insulating from the turbulence around AI. If I stared at AI and said, what could I do with it? You wouldn’t do what you just described. If you started with a solution, say, how do I make it better? How do I make it unmatched? By the way, there are three more vertical LLMs and other new goals that no one has thought about. But I can adapt and adopt it to do more. Then I should do that. It diminishes this fast evolution of the tech and says I’m putting it in the service of doing more for the customer.  

That’s my job. My job isn’t tracking the tech. My job is doing more for the customer, and it makes things clear and decision-making more focused when you adopt that logic. 

Paul 

Playing back your trifecta, how do we build our entire business model and our operations around this? In two points, it’s cost and growth. And how do we continuously evolve this? It’s not a one-time injection of AI or tech. How do we completely reinvent the way we operate? 

Rick 

Paul, we would be totally remiss if we didn’t talk about humans. What I mean by that is there’s this important muscle that you’ve just articulated. I want to draw it out and underscore, which is this muscle of rapid course correction and adaptation. This is not a leadership trait or a muscle that is well understood and activated in most incumbent organizations. Most incumbent organizations are rewarded for sustaining the mode, not finding the new mode. For this rapid course correction, doing it in a way that humans can sustain the change, understanding that if you’re going to move an organism from its old way to a new way, it’s going to take a lot of nudging. You can’t whack at it and hope to get it to the new state. You’re going to have to be able to say, okay, now you’ve started to collaborate cross-functionally, cross product, focused on an outcome. That’s great, but now how do we set the next OKRs, and what do we do to shift incentives to promote more of what you’re doing that leads you to a better future? 

Again, an example from my Microsoft experience, I thought it was fascinating to see when and how, in sequence, shifting the incentive system had so much to do with promoting greater collaboration across the organization, which was critically important to showing up as “One Microsoft”, which was the watchword. But it was all in time. Going straight to incentives isn’t the answer. Standing up the right apparatus – I call it an accelerator – to test and learn across all management dimensions, technology, AI, and thinking through the lens of the customer. These things require different behaviors and spaces in which people can learn quickly.  

Every company’s model for how they get to the future is going to be different, because it’ll be culturally appropriate. There’s no one-size-fits-all there, but I just wanted to underscore that we would be really remiss if we didn’t call out the importance of change and approaches to change. Which I think is different. In other words, you have to change the way you change to move into this AI future that we’re talking about. 

Paul 

That’s fascinating, and I would like to again reference the four zones where every zone requires different metrics for success, different leaders, and just different motions, in general. Maybe shifting to our third act here on “what ifs” and big bets. Thinking about our insurance and broader financial wellness space, if you fast-forward a few years, what’s your view on what will feel radically different? Feel free to go either in terms of how insurers would serve their customers or how customers would also engage. What are your big bets for the next few years? 

Rick 

Paul, this is a tough one for me, because for so long, I’ve lived in this world of looking at many of these gnarly problems that are underserved in insurance. There is this challenge of historically being able to really play the balance sheet and to really make this be about safeguarding the future.  

However, if I’m going to be a financial wellness provider, it means that I’m a very different-looking company than the insurers of today. I think of really difficult decisions around: how do I save for a rainy day, how do I reduce my debt, how do I begin to think of placing bets on my future retirement? If I’m heading to that age, I care a lot more about that. If I’m early in my career, I’m probably thinking more about a home and a family. Understanding those things that, to me, are a holistic financial security proposition. Having a company break out and redefine the category is what I’m really excited about. I’m always excited about – is there a way to redefine the category you’re in? I don’t see any reason to stop that or prevent that. AI can be a great vehicle for redefining the category you’re in and unleashing a whole next wave of growth along the way. I would love to see that happen. 

Paul 

There are some of these big problems that we’ve been talking about for quite a while. Retirement is bound to become a greater problem. People are living longer. The birth rates are declining. People have more dependence. The problem is there, and it’s not a problem that is just changing overnight. It has been building up for a long time.  

When looking at insurance and the broader financial services industry, there is almost the notion that insurers are somewhat safe, because it’s difficult even for big tech to replicate what it’s doing. But if you push forward what you are saying about demand aggregator, ecosystem orchestrator, and component supplier, there is a risk for the insurance industry to get commoditized to just being a capital provider. Somebody else is busting up the value chain, reorienting around the customer needs, and taking the lion’s share of the profit and the attention from the customer while getting supply from an industry that’s dwindling and dwindling. 

Rick 

Paul, we’ve seen some signs of this already. If you think of some of the big captives in the world that are powering growth in problem-solving in new spaces. Amazon has bought One Medical. That’s interesting. That’s not e-commerce, that’s not even selling cloud services or workloads on the cloud. You’re starting to see movement toward knitting together solutions for different ecosystems and different sets of customer needs. If the demand migrates to solving problems, then the notion of insurance and risk management is tied to that: what does an insurer do to participate in a world where that attention is moving to different ways of engagement powered by different data sets?  

I think this is something critically important. I do think the pace with which that engagement has migrated and how fast it can accelerate in the AI world is very real. From an old marketer’s perspective, again putting back on the adtech hat, we used to think about strong and weak signals and then building a signal factory to figure out a customer’s intent. That’s what we were trying to do. A strong signal is the search query. A weaker signal is the time you spent on the engaged web or dwell time on a website. We try to infer from that your intent. Inside this substrate of chat is all my intent, and my intent with memory. This is important to me to understand it for what it is. To figure out how I need to be present in that substrate to be increasingly relevant for higher-order problems. Again, not sky is falling, but boy, don’t wait. I think it’s somewhere between there. 

Paul 

If I look at the next 12 or 18 months, maybe even the next six months, what are the big shifts that you anticipate? What are we going to be seeing a lot more of, and what would you say executives should get ready for? 

Rick 

Having lived through waves of technology – and certainly I learned this in the dotcom bomb era – big things and big ships don’t really become big unless there’s enterprise monetization. I tend to focus my attention on players like Anthropic or Gemini, not because I like them or I’m saying they’re going to win, but because I think they’re really focused on solving enterprise problems. 

I think the enterprise has mostly been learning. I was going to say dabbling, but that would be wrong. I think giving tools, getting people acculturated and figuring out what we can do with Copilot. I think it’s so important to be aware of what’s possible for me in this world. There’s something about the end-to-end workflows, how those could look and could get AI-powered and what the outcomes would be, if I did that holistically end to end. I think of that more as a reimagining or a reinvention of a challenge. I’m hearing and sensing more of “Yes, let’s take that on.” That will be critical for unleashing value, because it means that what’s on the other side of the rainbow is humans who are then amplified or augmented in some new workstream. That may be inside the enterprise and outside the enterprise for activity streams. That is what they’re going to get to: not replacing people, but having people doing very different work, augmented, amplified, and enabled. I think we are barely there. We’re just scratching the surface and what that can be. I think looking forward, I would expect that we’ll see much more truly digitized and algorithm-driven enterprise, and enterprise monetization. 

Paul  

One thing we didn’t really talk about in the last hour is that AI is just for cutting jobs, which oftentimes tends to be the shortcut. It’s more about how you augment humans. But that also means if you want to be the human who’s augmented and enabled, your job description might be completely different tomorrow than it is today. There is a transformation. You were saying, let’s keep the human in the conversation. 

Rick  

The skillset has to evolve. There’s no question. Back to the point about an accelerator model and the building of the new muscle. It’s not just about learning the skills. It’s about applying them, trying them on, and marinating in them to test and learn. Last I checked, the pace of adoption is as fast as humans can adopt. How fast can humans adapt and adopt? I think faster, but I think ways of working inside of enterprises have been particularly difficult to change. How do we unleash people who now have a sense because of their chat interactions at home and on the go? How do they begin to think about imagining a very different workplace, and can that allow them to go from the back foot to the front foot? 

I was in some discussions with treasury functions. On one hand, being highly regulated and used to having to do so much work to just make sure everything is spot on, as opposed to: I can be a risk adviser and be on my feet to understand what the balance sheet effects might be of some geopolitical development. That’s a very interesting thing, because it creates truly interesting work and a role that is currently impossible for a whole range of reasons. Anyway, I think that notion of back foot and front foot and new work is quite exciting, but I think we’re going to have to invent our way there. It’s going to be difficult and hard work. 

Paul 

Maybe just to close – would love to get your final words of wisdom. As you think about the AI revolution playing out, what advice would you have for insurance executives? What words of wisdom would you leave them with? 

Rick 

Maybe I’ll say three things. First, figure out how to be both bold and provocative and incredibly pragmatic at the same time. The example I often give is when I was doing the startup thing, your venture investors want you to walk in the door and pound the table on how you see a new category, and you’re going to be the category killer. Then they go tell all their other venture investors over lunch. You have to be incredibly capital efficient, like the proceeds of your money come Monday morning are going to be gone. So that bold and pragmatic thing is a very difficult thing to do, because it’s going to take both. 

Second is to be really aligned, and we talked about this earlier, that the leadership team sees the future, not to say that they got it right, but they should see it the same way. They are clear-headed about how fast they need to move with the risks. That is going to be incredibly important. 

The third thing I’d say is, over many years, we’ve allowed the strategy and direction setting to live in one place, and the operating model and operationalizing is somebody else’s responsibility. It’s going to be important to keep all these things in lockstep and have a very compelling narrative, both externally to investors, which would also be a change narrative, and a way of mobilizing people internally. Those would be my three big hopes and wishes. 

Paul  

Rick, thank you so much for your time. It was such a pleasure having you with us. 

Rick  

It’s always great to be with you, Paul. Thank you so much. 

Paul 

That was Rick Chavez, partner and Customer First leader at Oliver Wyman. I am Paul Ricard. Thanks for listening, and I’ll see you next time. 

This transcript has been edited for clarity. 

Oliver Wyman Partner and Leader of Customer First, Rick Chavez, is an innovator with two decades’ experience at the forefront of the digital revolution. His experience spans a wide range of organizations — from pure start-up ventures through to $80 billion global corporations — as senior executive, advisor and Board member.

Rick focuses on helping senior leaders unlock the potential of this next wave of AI-triggered disruption to drive customer value and investor enthusiasm. He has significant expertise applying proven methods for “dealing with disruption” – pressure-tested in the tech sector – to the challenges of growth and reinvention for executives in banking, insurance and technology. He led the design and launch of new entities to harness disruptive forces: a NewCo for a major US life insurer and a multi-billion-dollar NewDiv for a leading mobile carrier. 

Rick collaborates closely with industry thought leader Geoffrey Moore, with his commercialized management models for growth and innovation  forming the basis of case studies in Moore’s recent books, Escape Velocity and Zone to Win, which serve as essential playbooks for digital innovators in the tech sector and beyond. He has authored unique points of view and was a frequent keynote speaker at major industry events such as MomentumAI Finance conference, TedX, AdWeek, Ad:Tech, ARF Re:Think, ProXXima, and Cannes Lions.

Oliver Wyman Partner and Head of Asia Pacific Insurance and Asset Management, Paul Ricard is based in Singapore. Paul works closely with businesses to reinvent their strategies, products, and services — and to fuel top-line growth opportunities.

He works with clients across Asia Pacific, as well as the Americas and Europe. He regularly partners with firms to reinvent their business strategy, rethink their priorities, and to modernize their technology while accounting for rapidly changing customer needs. He understands his clients’ realities, and thrives on helping them innovate and strengthen relationships with their customers while factoring existing challenges.

The insurance industry is under intense pressure to reinvent itself as rising customer expectations and rapid advances in AI redefine how value is created.  

In this episode of Reinventing Insurance, Rick Chavez, Oliver Wyman partner and leader of CustomerFirst, talks about putting customers at the center of AI‑enabled reinvention. Drawing on his experience leading large-scale technology transformations and innovation, Rick explains why insurers should start at the endpoint of the demand chain, take explicit positions on where to play, and reallocate management attention across four operating zones: performance, productivity, transformation, and incubation.  

The conversation walks through the “AI trifecta” for customer value, the trade-offs between being a demand aggregator, an ecosystem orchestrator, or a component supplier, and how AI can make personalized financial wellness and retirement solutions more accessible and affordable. 

Key topics include:

• Prioritizing which business areas to modernize, which to manage into obsolescence, and where to place one material bet at a time. 
• How to design operating models, incentives, and accelerators to test, learn, and scale AI‑driven customer propositions. 
• Practical thinking on demand aggregation, ecosystem orchestration, and building component products that plug into broader customer solutions. 

This episode is part of our Reinventing Insurance series, a series that explores best practices for taking a CustomerFirst approach to innovation within Insurance. Throughout this series, host Paul Ricard discusses lessons, challenges, and new ways of working with guests who will share their first-hand experiences.

Subscribe for more on: Apple Podcasts | Spotify 

Putting customers first as AI reshapes the insurance future

Paul Ricard 

Welcome to Reinventing Insurance. Today, I have the pleasure of welcoming Rick Chavez, partner and leader of CustomerFirst at Oliver Wyman. Welcome, Rick. 

Rick Chavez 

Thank you, Paul. It’s great to be with you. 

Paul 

Rick, you’re not foreign to the Reinventing Insurance Podcast. I think you recorded an episode with my colleague, Mick Maloney, a little while ago. 

Rick 

That was fun. 

Paul  

We’re going to look to top that today. For those who haven’t listened to it, Rick previously talked about customer-led reinvention, his experience with the Microsoft transformation from the inside, and many other themes. We’ll have a few callbacks to these as we talk today, but our focus is going to be about being customer-first in the age of AI and where insurance goes next. Before we unravel what we’re about to discuss today, we’d love for you to briefly tell us about yourself, Rick. 

Rick 

The place we’re in now is so fascinating to me. I dabbled in what was then called an ARPAnet – now called the internet – before it was even a commercial phenomenon. If you can imagine, I’m that old. I was also dabbling with early AI, and that is another one of these curiosities, because a lot of the algorithmic innovation that we are able to enjoy now, in terms of its activation and applicability, was actually pushed hard in the 80s, but it was back in a time when we were so completely wrong about how to use it. Our theory about using these algorithms for good was not wrong; it was simply at the wrong time. Watching things evolve through the years and seeing the evolution of technology has first sobered me, and still broadly encouraged me and made me an optimist. And I’m still an optimist, Paul. It’s sometimes hard to maintain optimism, but I’m still a glass-half-full kind of person. 

In terms of my story, I stumbled into management consulting out of college. I found that I was reasonably good at it, and I liked it. What was the most interesting thing about it, for me, was that it was a great vantage point to see things in the world that you want to fix, or that you think just don’t make sense. So, I jumped out, did a startup, sold that, then went back to consulting to detox. Found another idea, jumped out and built a company at a time I call ”the great happiness internet 1.0”. All boats are rising. It was actually not a time I predicted. I was just building a great company that was hopefully going to do great things. Then the dotcom bomb was quite painful at the time, but incredibly informative, like an incredibly important learning experience for me. I took some of the ideas that I just couldn’t let go of, and they stuck with me as I went west.  

I was on the East Coast for a long time building the startups. I went west and got to work very closely with Jeff Moore (Geoffrey A. Moore), who many people know is the guy who wrote “Crossing the Chasm”, and is often thought of as the father of innovation. He is very well known on the West Coast and tech companies, but completely unknown on the East Coast. We both got very interested around the same time in innovation at scale – me from having been a startup fellow, and Jeff from having been a venture investor. We were interested not in the challenge of being a startup, when you’re being incentivized and pushed to grow with no existing stakeholder commitments. That’s what startups are.  

What happens when you’re Cisco or SAP or Yahoo or Adobe, which were clients, where the company has grown to a place, and then growth has stalled out? How do you reignite the engines of growth? I tell you that because that passion or that interest became a passion, and it stuck with me to the present. It took me through two tours of duty, one at Adobe launching what was then called Customer Experience Management and morphed into the Marketing Cloud Business of today, which is amazing. Then, as you mentioned, I was part of the transformation effort at Microsoft as Steve Ballmer handed the keys to Satya (Nadella, CEO of Microsoft). I got there by having friends at Yahoo who had reported themselves as the search team at Microsoft. 

I brought that thinking about dealing with disruption and living through transformation to my work at Oliver Wyman. CustomerFirst, to me, is really all about dealing with disruption, with a very strong view that if you start at the endpoint of a demand chain, where people are either in a workflow or at home or on the go, have big pressing problems to be solved, which could be solved better with a digital experience powered by data. That essential thesis of dealing with disruption, by looking at customers’ problems, I would argue has been a passion pre-Oliver Wyman, but certainly has been a passion as I’ve been here. 

Paul  

You’re basically threading the needle with what we’re about to discuss. You’re helping large incumbents dealing with disruption and with innovation at scale, which I think you’re starting to allude to – there is a method to the madness. 

Rick 

There is a method to the madness. I do like to say that the best entrepreneurs, the best innovators, are the most disciplined people you’ll meet. It seems to be a conundrum because I think many people who work in innovation think that this is fun. Truthfully, if you’re doing it in its truest form, it probably hurts. And that’s probably just about right, because it should be a very systematic, thoughtful test-and-learn discipline approach. I think the doing of it, and doing it right, is critically important and is something a lot of our clients are still developing and working on. 

Paul 

It’s not just the free soft drinks and the sneakers in the open space. It certainly seems like there are a lot of tectonic shifts that are happening. I know you like to talk about the collision of megatrends, and it feels like this is something that is continuing to happen and accelerate. Can you tell us a little bit what’s happening and what feels different? 

Rick 

Let me start by first saying some of what’s happening now was predictable. Any disruption, if it truly is a disruption – and you mentioned this is a collision of megatrends – that needs shifts in behavior, along with maybe societal, political, and regulatory things that are happening. Technology, I like to think of it more as a tailwind as opposed to the main event. The reason is that if you stare at technology as is the case right now in this AI moment, no matter what we say about what will be three months from now, we would be completely wrong. 

If you look at that collision and you say, all right, what is enduring about humans in their work and their attitudes and approaches to digital technology that either allows more of what they want, and less of what they don’t want to be part of their lives. I would say, first of all, that’s enduring. I’m going to come back to that. Second, that’s what’s so radically different about now versus then. We’ve never had as much digital familiarity. If you think about it, you have extraordinary familiarity with all things digital. We carry around supercomputers in our pockets. They’re connected as if they’re another finger and appendage. 

The second thing is connectivity. Pervasive connectivity. If you think about what’s happened in evolution after evolution, we have 5G, we have fiber. These things really, really matter because it means that those edge devices can do more, and they can do more that then help us be more. You have this context of pervasive connectivity that allows for very rich experiences, which we expect, and we actually want them to be intelligent. I will assert that most of the experiences have not been intelligent. Most of what we say about smartphones is, frankly, more dumb than smart. I’m sorry to say that. But the reason I say that, now that intelligence can be pushed out in the AI economy, you have people hungry for that thing and having expected it already. So that’s why this meteoric adoption of all things chat, whether it’s OpenAI or Claude or Gemini or OpenClaw, why does it look like it's instant? I think it’s because people have been expecting this kind of engagement with the world for a very long time. 

Think about it this way. You and I have been taught to use a keyboard. We’ve been taught to use our thumbs [for smartphone keyboards]. Neither of those things is particularly human. We’re okay with them, but they’re not particularly human. In this world, what’s showing up is the other thing that’s happening with adoption, making it human and natural, like the interface is my voice. This, too, is such a stunning thing because in 2001 or 2002, I was CEO of the first multimodal company that invented multimodal. We thought then, too, that it was going to get dispersed quickly. Think about how long it took. It’s this NLP natural language interaction model with deep intelligence embedded in the fabric of the world, and its ability to be dispersed and then onboarded into our lives is completely different. That is a phenomenon that is unique to this moment. 

Paul 

You are saying that it’s so enduring, and people are experiencing this at scale in their day-to-day lives. What is interesting is that there is an expectation that if a company is going to engage with me, either to solve my problem, to sell me something, or to interact with me, it’s going to feel the same way these things have felt. I would love your take on this. It feels very similar, for example, to the iPhone moment when the iPhone came out. Now, suddenly, if a company is not engaging with someone through an app, you are dead on arrival. The web 1.0 interface was… 

Rick 

became the mobile app. Exactly. That’s 100%. 

Paul 

That’s one thing. At the same time – and I would love your take on this – what is also interesting is that the pace of change is so rapid that if you got used to something two months ago, it is very, very different now. I’m also linking this to the expectation you would have from corporate, where you need to get up with the program more and more quickly. 

Rick  

The cycle time changes. Let’s take these two things because there’s a conundrum in there. One is that some things are enduring, which is to say that they’re not changing, and what does that mean? Then there’s an enormous amount of change in the cycle time, which has never been faster. We have both these things at the same time. 

I think, first, let’s take the enduring one. I do believe that the big vexing problems in the world are largely still underserved. Let me put my marketer’s hat on. Let’s pretend I’m back in the adtech days that I came from. One of the nirvanas was – if Paul’s driving along home, and it’s been a long day, and he was expected to be the dinner preparer. There’s no way he is going to be able to do that in time. But I know that Paul takes a certain route and has a certain expectation. He’s a little late actually getting home. I wonder if I could surface an offer to him to stop at some really interesting place that has the cuisine that he can pick up at home. Would that feel like magic to you that it not only knows you and your habits, but that in fact you’re kind of anxious and a little bit upset at yourself that you’re getting home late. That is an example of intelligence serving you a thing that might make a lot of sense, that you can then wrap around that moment to do something you would otherwise not have been able to do. That is the solving of a problem. And that’s been a marketer’s nirvana for a very long time. 

I think there’s a whole range of problems like that. The new intelligence environment and the ambient intelligence should be unleashed. There are still a lot of these big problems that are not solved. Like we’ve talked about this a lot: how do I solve for retirement? In my case, it might be very complex. My spouse might have one idea. I might have another. We might have to think about our kids, maybe with the sandwich generation, there are all these different kinds of considerations. No one is exactly the same. There are patterns that may rhyme, but they’re not explicitly the same. If I look at that problem, I would say, Jeez, [I would love to have] some intelligence around nudging me in one direction or another, or alerting me, or even making it simple to have a unified view of my financials. These are nontrivial problems.  

So, if I look at what the undiscovered country is and the potential for new customer value, I would say lots. And you know this too, because I’ve used the example of other companies that have really gone after the problems that you said, versus selling the products they want to have. Like them or not, Tesla really isn’t a product seller. There is a thing called the Tesla, and it’s got different models. But the problem it solved was this sense that some people had about being electric, not petrol – that might have been a preference. Also, I don’t want to go to a dealer to buy a car, and I’d not like to go to the dealer to get service either. Downloadable software while it’s sitting in my driveway charging – that sounds pretty good. It’s the complex of those needs I have that they were able to capitalize on to create this extraordinary value. 

Paul 

It is interesting because, to your point, drawing the parallel, it’s in a way, Tesla, as an example, has solved multiple problems at once, broken through the entire value chain all the way from the dealer to the car manufacturer, to now even the entire ride-sharing industry as well. 

Rick  

100% absolutely. By the way, Paul, just to tap on that, the value chain is a construct of a supply-side world that says this is the way I built a product and I get it to market. Demand chain disrupts all that, because it’s how I think and want. And that’s what you just described that Tesla did. As a result, look at all this disruption. 

Paul 

Building on this, and thinking about our insurer friends, in a way, there is a very interesting parallel here. Retirement is one thing, financial wellness, financial security, not only for one’s financial wellness, but for one’s entire family. The way the industry has solved this for a huge amount of time has been more product selling than problem solving. Even in cases where it was problem solving, it was more of “let me solve that one sliver of the problem, versus all these things. I’ll go back to something I was saying earlier that AI is moving so quickly, and I’m being very cautious because I don’t want to make it sound like it’s this magical solution. It’s very complex.

One of the questions, for example, is whether these things are so complex that we would need a human in the interaction? Maybe. For the time being, that is probably the case. But even if that’s the case, the way humans are engaging with a customer, the breadth of the needs that they’re able to understand of the individual customers and their family, whether it is a point in time or over decades, and obviously, the breadth of solutions that they can provide and hyper-personalize and customize. I think there is a radical shift here that is in the process of happening. 

Rick  

And I would say it’s happening at much lower costs. So much more accessible and affordable. I can actually start with customer value work back and do it more efficiently and effectively with a greater cycle time. 

I wanted to make sure that I completed a thought, which I didn’t, because I got excited about only one part of my answer to your prior question. I do think that there’s also this adage of never confusing a clear view for a short distance. I think what you just talked about, family and financial wellness, triggered by life events through a period of time, is potentially a point of arrival or destination that says I’m going to do more of that. I’m going to do it with maybe more of this available smart that exists in the fabric of the world. Now, what is the set of experiments? How do I test my way to get to that different future?  

I think this is where, in picking up the cycle time of change, we talked about things that are enduring and then things that are really changing. I think the best path to dealing with uncertainty and volatility in the environment is to stare it in the face and say, I have a hypothesis. It’s a belief about how things are heading. Now I could be wrong, but I’m going to be in the game and actively engaged in learning as I go. I’m going to learn as fast as I can, because the faster I learn, the better off I’ll be. That agility is hypercritical as the world changes fast. The ability to then not only meet and master it but master it for your own hypothesis about where you’re heading and why you should be winning in that future. 

Paul 

Diving into this, I would love to get into your playbook for what this looks like. I think you’re calling it “AI trifecta”. What does this look like?  

I’m also reflecting before we shift to that – what I find interesting is, again, I was talking about the iPhone comparison. I’m old enough to remember when iPhone replaced Blackberry in corporations, and it was very much employee or individual pushed, which was: I have access to this, therefore, I don’t want to use these tiny keyboards. I want to have a richer interface. Interestingly, as a customer now, we’ve done some research around this. The majority of individuals nowadays are using AI for some form of financial advice. Now, is it the full picture? Is it fully regulatory compliant in terms of the type of answers you get? Is it as sturdy as a proper and well-accredited financial advisor will provide you with? Probably not, but it is priming the pump for, to your point, what it can look like. Also, it has a very different cost structure. It’s a very different cycle time. It’s another shift. That’s customer-led basically. 

Rick 

You’re correct. There’s tremendous uptake. One thing you and I have learned together, on some prior work we’ve done, is that money is emotional. That has lots of implications, including I don’t want to be embarrassed by what I don’t know. Where I think AI engagement around money matters is interesting is that AI is not a judge; it doesn’t judge me. If there are a lot of things I don’t know, it’s not telling me "you idiot, you should have known all these things". I can be private in my ignorance and potentially close that gap. Financial literacy continues to be an incredibly pressing problem. I can see some advantages. I think the dark side of that, though, is if you’re not good at prompt engineering, what do you do with it? I think there’s a lot to be said for domain-specific advice and guidance. 

Paul 

There are an insane number of opportunities for incumbents to take on that challenge and offer something that is a lot more valuable. How do you see the big questions that incumbents need to think about as they think about AI-led customer transformation? 

Rick  

I think that in times of great change, if we don’t have a plan, don’t be surprised if you show up underwhelming. I think having this chat with you about the whole creation of robotics, for example, in China – I am fascinated, I’m just a student, I’m a learner. What’s fascinating to me about that plan that created the robotics industry, particularly around manufacturing, is it was a very long view of how things might develop, including how cultural shifts would occur and what jobs people might and might not want, what that would mean for a workforce on a manufacturing assembly line versus not. It wasn’t just that it’s been an extraordinary innovation, but it was planned thoughtfully. 

I think one of the most important things to do in times of real change is to have a view about where the puck is heading and its course and speed. Take a position. It doesn’t mean that you’re going to be right. This is interesting – it’s not the illusion of infallibility or that you have a crystal ball, but for this notion of collision of megatrends, the megatrends actually already are observable, and so the ideas play them forward. Be thoughtful and rigorous in saying, what do we think is going to happen in 2030 based on what is already observable? Let me stand there and look back to the present and understand what crown jewels I really have? What differentiates me? What am I doing that could eventually be a crown jewel? Should I accelerate it or not? But stand in the future, look back and then say if I’m heading into that 5-year horizon with some velocity, with some competitive separation, what would I need to do over the next 18 months, and does my current plan or record position me to be doing those things?  

If not, I'd better start to challenge it and shape it. I think the number one play is to do that, I think it is so important. And again, not to pretend to be right, but the leadership team is aligned and saying the same thing with the same words that have the same meaning. 

Paul 

As you figure out where to grow and where the puck is headed, there is an element of being clear about what trends we’re going to see. Potentially, what’s also going to become extinct. If you are, for example, surveying the populations that are in their 20s and 30s, but the population is structurally getting older, then you can see your own market suddenly dwindling, and at the same time, there are greater needs in the longevity space. That’s why I liked your example of robotics. Given the policies and everything in China, we could see the manufacturing workforce dwindling over time, so it has almost become a necessity to work on robotics. 

Rick 

If you decide that you’re going to compete and be differentiated, then this is a thing. A bet that you really have to place. We like to say: make an asymmetrical bet about that. Others either cannot do or will not do, which certainly happened in that case. 

Paul  

I want to pressure test this with you. There is an element of where you are going to play, and therefore, how you are going to further build your competitive modes. Potentially starting to think about what’s likely going to become over time, either deprioritized or commoditized. 

Rick 

No longer part of the future? I’m glad you brought that up, Paul, because I think that’s probably the most difficult thing to do. When you do that, “play it forward and let me see if I am heading on the right path and the right speed,” it is to look at the portfolio businesses and say some of the things that took us to our present are just simply not going to be a big part of our future.  

This is my learning about the Microsoft experience – that desktop office was simply not going to be part of the future. It just didn’t give us any insight into what humans really wanted to do, so we said we'd better let that go, put on life support, and race to build Office 365. I think every company has these moments, they call them “cash cows,” or they’ll use whatever words they use, but they know what things they’ve been hugging that have been big but are no longer growing and are not part of the future trajectory. I think being honest and then saying I’m going to open my eyes and clinically and dispassionately manage it into obsolescence, maybe even divest it, because I’ve got to let it go that fast. I think that is one of the most important decisions, because unless and until you do that, it’s hard to fund the future. You can’t carry forward a cost structure where you keep ending everything like that. You have to be able to fund the future. 

Paul 

One of the big challenges that you and I have spent a lot of time discussing is: it’s not even just dollars; it’s also management attention. 

Rick 

The hardest and the scarcest of all. That’s exactly right.

Paul 

And how it is extremely easy to overallocate management attention to what you call “productivity zone” or “cash cows,” while underallocating what could be the bets for the future that are not quite yet at the scale that you need, but deserve that attention and funding at the same time. 

Rick 

Now you’re getting at the management discipline that it takes: continuing to honor stakeholder commitments in the present, downshifting from things that are going to take me to the promised land, and developing a muscle about systematic test-and-learn.  

This is why I’m such a believer in this four-zone notion. The performance zone is BAU. The productivity zone is “I’m going to manage things into obsolescence, make things extraordinarily efficient and the best”. Then the incubation and transformation zones are where I’m going to place bets about reinvention and/or growth, but probably in a portfolio of 10 bets, probably six or seven of those should be on reinvention, and maybe a couple on growth. Then I’m going to push one and only one bet at a time to materiality, because I don’t want to find myself in this place where I’m trying to push two or three things that get mid-size, but never quite break out and get escape velocity.  

Let’s get everybody focusing on making a thing material. And if we can do that, then let’s do two. Once I do one, let’s do two. I think that notion that all those zones take the right management attention, to your point, each of those zones has unique metrics. Each of those zones requires a certain temperament of a leader. If you don’t have great optimizers who are managing the productivity zone, don’t be surprised if it’s very difficult for the applied innovators and deployers to be successful. It’s because you’re asking them to do things that are simply unnatural and not possible. I think honoring all of those management archetypes and really having the right metrics zone by zone is so critical. 

That’s a new thing. For many companies. It’s not necessarily so new in tech. This is why I have a certain passion, having seen it in tech. In the tech sector, you’re rewarded for growth. You’re rewarded to go find the next big growth opportunity, where that’s not necessarily been the case in insurance. I think building the muscle that says it’s about low growth to high growth categories, and I’m going to actually start to do both things and be an expert. I think that is an interesting and important challenge, but an essential one when the world is changing quickly. 

Paul 

Building on this, we talked about where to grow, where the puck is headed, and therefore where you want to go. As we go into where to play, I’m going to set you up here a little bit. I know you like to talk about demand aggregators, ecosystem orchestrators, and component suppliers. If I look at insurers, they’ve typically been more of a component supplier in a broader ecosystem, sometimes in their own ecosystem if they had the front door, sometimes in somebody else’s.  

Things are evolving. We just talked about this – how to think about where to play. My inherent bias from the outset is that being a component supplier may not be the right place to be, especially if it’s almost a default decision. There might be some elements where you actually choose to be a component supplier that has these advantages and has a very clear view of how the broader ecosystem is playing. But I’m curious, where do you think the opportunities are, and what advice would you have for insurers? 

Rick 

I do think that where to play is so critically important. I do believe that there are these three [power positions]. We can give them whatever words we want, but there’s this demand aggregator notion of I am going to solve problems for Paul. Whatever Paul’s problems are, I’m going to solve them. I’m going to do it in an increasingly intimate, personalized, AI-powered way. That doesn’t mean I have to own the ecosystem or even orchestrate it, but I’m going to be that front door. Front door is not even a good way of thinking about it, but it’s almost the persona you go to around a set of needs, in this case, financial wellness. This notion of where to play is important, sector by sector or demand space by demand space. You don’t expect that the demand aggregator for medical purposes is going to be the same as your [medical service provider].  

That’s one, then there is the component supplier. You made a really important point, which is that defaulting to that is not a good decision. I’ll come back to it in a second. There’s a third place, which I think is really interesting, which is the ecosystem orchestrator. My job is to begin to get the hyper-scalers, the cloud, the fires, or the vertical solution players together to actually push a solution into the demand aggregator. And I’m going to source the components from component suppliers in an incredibly efficient and modern way. 

These three places – demand aggregator, ecosystem orchestrator, and component supplier – you can make money in all three of these. But they are an explicit choice, and there are very different skillsets across them. For example, that ecosystem orchestrator, in a lot of conversations with companies that think of that as a path to value, it often takes – I hate to call it “biz dev” because it seems to make it so pedestrian – the ability to actively engineer these relationships. If it’s going to be API-able, figure out what that is from a business standpoint before you go to the technology. What I mean by that is what are the give/gets, are those give/gets reasonable, and are there adequate decision rights? These are gnarly governance questions around that. That becomes incredibly important in differentiating skill and capability. Then the component supplier. If you’re trying to be a component supplier and you feel like your product can go into multiple ecosystems and serve many demand aggregators. That’s awesome. Think about monetizing. That’s great, but then should you have direct sales? Should you also work hard to own the distribution? Is that a sensible thing to do when you really need to make sure that your product is unbeatable and unmatched in terms of its economics and its ability to plug in and all these other things? I think being very clear about those, and making explicit choices on a business-by-business basis, is going to be critically important, especially in the age of AI. 

Paul 

It’s interesting. Just to take a couple of examples, it’s not about, can you do one without the other? It’s more about management attention, focus, and the capabilities needed to build; it takes a lot of effort. Being a component supplier is not an unrealistic place to be, but being able to say, I’m going to upgrade my insurance products once a year, I’m going to just make sure I have the right economics, I have the right investment solutions behind us – that is not enough anymore. You want to be able to hyper-personalize individual customers of different customer personas or archetypes.  

Even if you’re a component supplier, in insurance and financial services, the product could be more. It could be the insurance product, the economic promise to the customer, but also the digital engagement that comes with this or a series of services. We’re talking about retirement. That’s where you can start linking a lot of different things. That is something that, for the majority of companies, is going to require a massive shift in the operating model. Back to your point – are you committed to this, and are you committed to building all the right capabilities to build those competitive modes so that you do not get commoditized? 

Rick 

That’s right. As you decide where to play business by business, really think from the customer archetype – the family unit contemplating retirement and sandwich generation issues. Work back from that and say, what would the set of solutions need? Can I source some of those pieces from the ecosystem using agentic orchestration, as opposed to having to do everything myself? Does that liberate me to be excellent at the products where I am truly differentiated to the point of competitive mode? Let me light the way to the core shared capabilities that should be present and only do those and/or reengineer their rebuild or reinvent those in modern technology, as opposed to dealing with all of the tech debt that I might have. Use that proposition and what we know customers want to pay for to show the way to how I’m going to go about delivering against it. It’s thinking about the operating model, yes, but outside in and using that as a lens to figure out what is, in fact, needs to be modernized, and how to modernize it. This is where I think the notion of new value, plus efficiency and cycle time improvement. You can get both. It’s not an “either/or” but both ends done properly. 

Paul 

If I look back to the last couple of years, a lot of players in insurance and financial services and beyond looked at AI, and I feel like, oftentimes, it was more of “on the fringe” or a tech thing. While the way we’re talking about this here is – you need to start from the business problem and the customer problem. There is a very active choice to be made about how you are going to be using AI to accelerate the build of your new capabilities. And to your point, it’s both ends – cost and growth. 

I’m going to go back to my component supplier example. To me, using AI should be in service of “we have decided that we want to be a component supplier that’s going to be providing the best solution that is tailored to the exact need of each person, given their situation, their family needs, and where they’ve been and where they want to go on their financial roadmap, and even on their non-financial roadmap as it’s not about just financial needs. Therefore, everything we want to do is to better understand all these needs and tailor them. Therefore, any AI investment we make is in support of that. And it’s not a once-and-done thing. 

Rick 

I want to pause on it or underscore it, because right there lies all the difference in value from AI or insulating from the turbulence around AI. If I stared at AI and said, what could I do with it? You wouldn’t do what you just described. If you started with a solution, say, how do I make it better? How do I make it unmatched? By the way, there are three more vertical LLMs and other new goals that no one has thought about. But I can adapt and adopt it to do more. Then I should do that. It diminishes this fast evolution of the tech and says I’m putting it in the service of doing more for the customer.  

That’s my job. My job isn’t tracking the tech. My job is doing more for the customer, and it makes things clear and decision-making more focused when you adopt that logic. 

Paul 

Playing back your trifecta, how do we build our entire business model and our operations around this? In two points, it’s cost and growth. And how do we continuously evolve this? It’s not a one-time injection of AI or tech. How do we completely reinvent the way we operate? 

Rick 

Paul, we would be totally remiss if we didn’t talk about humans. What I mean by that is there’s this important muscle that you’ve just articulated. I want to draw it out and underscore, which is this muscle of rapid course correction and adaptation. This is not a leadership trait or a muscle that is well understood and activated in most incumbent organizations. Most incumbent organizations are rewarded for sustaining the mode, not finding the new mode. For this rapid course correction, doing it in a way that humans can sustain the change, understanding that if you’re going to move an organism from its old way to a new way, it’s going to take a lot of nudging. You can’t whack at it and hope to get it to the new state. You’re going to have to be able to say, okay, now you’ve started to collaborate cross-functionally, cross product, focused on an outcome. That’s great, but now how do we set the next OKRs, and what do we do to shift incentives to promote more of what you’re doing that leads you to a better future? 

Again, an example from my Microsoft experience, I thought it was fascinating to see when and how, in sequence, shifting the incentive system had so much to do with promoting greater collaboration across the organization, which was critically important to showing up as “One Microsoft”, which was the watchword. But it was all in time. Going straight to incentives isn’t the answer. Standing up the right apparatus – I call it an accelerator – to test and learn across all management dimensions, technology, AI, and thinking through the lens of the customer. These things require different behaviors and spaces in which people can learn quickly.  

Every company’s model for how they get to the future is going to be different, because it’ll be culturally appropriate. There’s no one-size-fits-all there, but I just wanted to underscore that we would be really remiss if we didn’t call out the importance of change and approaches to change. Which I think is different. In other words, you have to change the way you change to move into this AI future that we’re talking about. 

Paul 

That’s fascinating, and I would like to again reference the four zones where every zone requires different metrics for success, different leaders, and just different motions, in general. Maybe shifting to our third act here on “what ifs” and big bets. Thinking about our insurance and broader financial wellness space, if you fast-forward a few years, what’s your view on what will feel radically different? Feel free to go either in terms of how insurers would serve their customers or how customers would also engage. What are your big bets for the next few years? 

Rick 

Paul, this is a tough one for me, because for so long, I’ve lived in this world of looking at many of these gnarly problems that are underserved in insurance. There is this challenge of historically being able to really play the balance sheet and to really make this be about safeguarding the future.  

However, if I’m going to be a financial wellness provider, it means that I’m a very different-looking company than the insurers of today. I think of really difficult decisions around: how do I save for a rainy day, how do I reduce my debt, how do I begin to think of placing bets on my future retirement? If I’m heading to that age, I care a lot more about that. If I’m early in my career, I’m probably thinking more about a home and a family. Understanding those things that, to me, are a holistic financial security proposition. Having a company break out and redefine the category is what I’m really excited about. I’m always excited about – is there a way to redefine the category you’re in? I don’t see any reason to stop that or prevent that. AI can be a great vehicle for redefining the category you’re in and unleashing a whole next wave of growth along the way. I would love to see that happen. 

Paul 

There are some of these big problems that we’ve been talking about for quite a while. Retirement is bound to become a greater problem. People are living longer. The birth rates are declining. People have more dependence. The problem is there, and it’s not a problem that is just changing overnight. It has been building up for a long time.  

When looking at insurance and the broader financial services industry, there is almost the notion that insurers are somewhat safe, because it’s difficult even for big tech to replicate what it’s doing. But if you push forward what you are saying about demand aggregator, ecosystem orchestrator, and component supplier, there is a risk for the insurance industry to get commoditized to just being a capital provider. Somebody else is busting up the value chain, reorienting around the customer needs, and taking the lion’s share of the profit and the attention from the customer while getting supply from an industry that’s dwindling and dwindling. 

Rick 

Paul, we’ve seen some signs of this already. If you think of some of the big captives in the world that are powering growth in problem-solving in new spaces. Amazon has bought One Medical. That’s interesting. That’s not e-commerce, that’s not even selling cloud services or workloads on the cloud. You’re starting to see movement toward knitting together solutions for different ecosystems and different sets of customer needs. If the demand migrates to solving problems, then the notion of insurance and risk management is tied to that: what does an insurer do to participate in a world where that attention is moving to different ways of engagement powered by different data sets?  

I think this is something critically important. I do think the pace with which that engagement has migrated and how fast it can accelerate in the AI world is very real. From an old marketer’s perspective, again putting back on the adtech hat, we used to think about strong and weak signals and then building a signal factory to figure out a customer’s intent. That’s what we were trying to do. A strong signal is the search query. A weaker signal is the time you spent on the engaged web or dwell time on a website. We try to infer from that your intent. Inside this substrate of chat is all my intent, and my intent with memory. This is important to me to understand it for what it is. To figure out how I need to be present in that substrate to be increasingly relevant for higher-order problems. Again, not sky is falling, but boy, don’t wait. I think it’s somewhere between there. 

Paul 

If I look at the next 12 or 18 months, maybe even the next six months, what are the big shifts that you anticipate? What are we going to be seeing a lot more of, and what would you say executives should get ready for? 

Rick 

Having lived through waves of technology – and certainly I learned this in the dotcom bomb era – big things and big ships don’t really become big unless there’s enterprise monetization. I tend to focus my attention on players like Anthropic or Gemini, not because I like them or I’m saying they’re going to win, but because I think they’re really focused on solving enterprise problems. 

I think the enterprise has mostly been learning. I was going to say dabbling, but that would be wrong. I think giving tools, getting people acculturated and figuring out what we can do with Copilot. I think it’s so important to be aware of what’s possible for me in this world. There’s something about the end-to-end workflows, how those could look and could get AI-powered and what the outcomes would be, if I did that holistically end to end. I think of that more as a reimagining or a reinvention of a challenge. I’m hearing and sensing more of “Yes, let’s take that on.” That will be critical for unleashing value, because it means that what’s on the other side of the rainbow is humans who are then amplified or augmented in some new workstream. That may be inside the enterprise and outside the enterprise for activity streams. That is what they’re going to get to: not replacing people, but having people doing very different work, augmented, amplified, and enabled. I think we are barely there. We’re just scratching the surface and what that can be. I think looking forward, I would expect that we’ll see much more truly digitized and algorithm-driven enterprise, and enterprise monetization. 

Paul  

One thing we didn’t really talk about in the last hour is that AI is just for cutting jobs, which oftentimes tends to be the shortcut. It’s more about how you augment humans. But that also means if you want to be the human who’s augmented and enabled, your job description might be completely different tomorrow than it is today. There is a transformation. You were saying, let’s keep the human in the conversation. 

Rick  

The skillset has to evolve. There’s no question. Back to the point about an accelerator model and the building of the new muscle. It’s not just about learning the skills. It’s about applying them, trying them on, and marinating in them to test and learn. Last I checked, the pace of adoption is as fast as humans can adopt. How fast can humans adapt and adopt? I think faster, but I think ways of working inside of enterprises have been particularly difficult to change. How do we unleash people who now have a sense because of their chat interactions at home and on the go? How do they begin to think about imagining a very different workplace, and can that allow them to go from the back foot to the front foot? 

I was in some discussions with treasury functions. On one hand, being highly regulated and used to having to do so much work to just make sure everything is spot on, as opposed to: I can be a risk adviser and be on my feet to understand what the balance sheet effects might be of some geopolitical development. That’s a very interesting thing, because it creates truly interesting work and a role that is currently impossible for a whole range of reasons. Anyway, I think that notion of back foot and front foot and new work is quite exciting, but I think we’re going to have to invent our way there. It’s going to be difficult and hard work. 

Paul 

Maybe just to close – would love to get your final words of wisdom. As you think about the AI revolution playing out, what advice would you have for insurance executives? What words of wisdom would you leave them with? 

Rick 

Maybe I’ll say three things. First, figure out how to be both bold and provocative and incredibly pragmatic at the same time. The example I often give is when I was doing the startup thing, your venture investors want you to walk in the door and pound the table on how you see a new category, and you’re going to be the category killer. Then they go tell all their other venture investors over lunch. You have to be incredibly capital efficient, like the proceeds of your money come Monday morning are going to be gone. So that bold and pragmatic thing is a very difficult thing to do, because it’s going to take both. 

Second is to be really aligned, and we talked about this earlier, that the leadership team sees the future, not to say that they got it right, but they should see it the same way. They are clear-headed about how fast they need to move with the risks. That is going to be incredibly important. 

The third thing I’d say is, over many years, we’ve allowed the strategy and direction setting to live in one place, and the operating model and operationalizing is somebody else’s responsibility. It’s going to be important to keep all these things in lockstep and have a very compelling narrative, both externally to investors, which would also be a change narrative, and a way of mobilizing people internally. Those would be my three big hopes and wishes. 

Paul  

Rick, thank you so much for your time. It was such a pleasure having you with us. 

Rick  

It’s always great to be with you, Paul. Thank you so much. 

Paul 

That was Rick Chavez, partner and Customer First leader at Oliver Wyman. I am Paul Ricard. Thanks for listening, and I’ll see you next time. 

This transcript has been edited for clarity. 

Oliver Wyman Partner and Leader of Customer First, Rick Chavez, is an innovator with two decades’ experience at the forefront of the digital revolution. His experience spans a wide range of organizations — from pure start-up ventures through to $80 billion global corporations — as senior executive, advisor and Board member.

Rick focuses on helping senior leaders unlock the potential of this next wave of AI-triggered disruption to drive customer value and investor enthusiasm. He has significant expertise applying proven methods for “dealing with disruption” – pressure-tested in the tech sector – to the challenges of growth and reinvention for executives in banking, insurance and technology. He led the design and launch of new entities to harness disruptive forces: a NewCo for a major US life insurer and a multi-billion-dollar NewDiv for a leading mobile carrier. 

Rick collaborates closely with industry thought leader Geoffrey Moore, with his commercialized management models for growth and innovation  forming the basis of case studies in Moore’s recent books, Escape Velocity and Zone to Win, which serve as essential playbooks for digital innovators in the tech sector and beyond. He has authored unique points of view and was a frequent keynote speaker at major industry events such as MomentumAI Finance conference, TedX, AdWeek, Ad:Tech, ARF Re:Think, ProXXima, and Cannes Lions.

Oliver Wyman Partner and Head of Asia Pacific Insurance and Asset Management, Paul Ricard is based in Singapore. Paul works closely with businesses to reinvent their strategies, products, and services — and to fuel top-line growth opportunities.

He works with clients across Asia Pacific, as well as the Americas and Europe. He regularly partners with firms to reinvent their business strategy, rethink their priorities, and to modernize their technology while accounting for rapidly changing customer needs. He understands his clients’ realities, and thrives on helping them innovate and strengthen relationships with their customers while factoring existing challenges.